{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Telco Customer Churn Prediction Kale\n",
    "\n",
    "In this [Kaggle competition](https://www.kaggle.com/datasets/blastchar/telco-customer-churn) \n",
    "\n",
    ">In this competition, your goal is to analyze behavior to retain customers and predict churning. You can analyze all relevant customer data and develop focused customer retention programs."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Install necessary packages\n",
    "\n",
    "We can install the necessary package by either running `pip install --user <package_name>` or include everything in a `requirements.txt` file and run `pip install --user -r requirements.txt`. We have put the dependencies in a `requirements.txt` file so we will use the former method.\n",
    "\n",
    "> NOTE: Do not forget to use the `--user` argument. It is necessary if you want to use Kale to transform this notebook into a Kubeflow pipeline.",
    "\n",
    "After installing python packages, restart notebook kernel before proceeding.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": [
     "skip"
    ]
   },
   "outputs": [],
   "source": [
    "!pip install -r requirements.txt --quiet"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Imports\n",
    "\n",
    "In this section we import the packages we need for this example. Make it a habit to gather your imports in a single place."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": [
     "imports"
    ]
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy import stats\n",
    "import seaborn as sns\n",
    "import wget, os\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from sklearn.utils import class_weight\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import confusion_matrix\n",
    "\n",
    "from xgboost import XGBClassifier\n",
    "from lightgbm import LGBMClassifier\n",
    "from catboost import CatBoostClassifier\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "pd.set_option('display.max_columns', 500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "5lzDgAyWWUpF",
    "tags": [
     "skip"
    ]
   },
   "outputs": [],
   "source": [
    "# Set random seed for reproducibility and ignore warning messages.\n",
    "np.random.seed(22)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Download and load the dataset\n",
    "\n",
    "In this section, we download the data from kaggle to get it in a ready-to-use form by the model. \n",
    "\n",
    "First, let us load and analyze the data.\n",
    "\n",
    "The data is in csv format, thus, we use the handy read_csv pandas method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": [
     "block:load_data"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/jovyan/WA_Fn-UseC_-Telco-Customer-Churn (1).csv'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# download files\n",
    "data_path = os.getcwd()\n",
    "\n",
    "# data link\n",
    "data_link = 'https://raw.githubusercontent.com/kubeflow/examples/master/telco-customer-churn-kaggle-competition/data/WA_Fn-UseC_-Telco-Customer-Churn.csv'\n",
    "\n",
    "# download data\n",
    "wget.download(data_link, f'{data_path}/WA_Fn-UseC_-Telco-Customer-Churn.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "mXgpsJKUi6al",
    "tags": []
   },
   "outputs": [],
   "source": [
    "# read data\n",
    "data = pd.read_csv(f'{data_path}/WA_Fn-UseC_-Telco-Customer-Churn.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "Let us now explore the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 211
    },
    "id": "gzBw5LOcjHZu",
    "outputId": "fffdccc3-9892-4fae-d75e-37d44fdf1312",
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customerID</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7590-VHVEG</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5575-GNVDE</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.5</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   customerID  gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
       "0  7590-VHVEG  Female              0     Yes         No       1           No   \n",
       "1  5575-GNVDE    Male              0      No         No      34          Yes   \n",
       "\n",
       "      MultipleLines InternetService OnlineSecurity OnlineBackup  \\\n",
       "0  No phone service             DSL             No          Yes   \n",
       "1                No             DSL            Yes           No   \n",
       "\n",
       "  DeviceProtection TechSupport StreamingTV StreamingMovies        Contract  \\\n",
       "0               No          No          No              No  Month-to-month   \n",
       "1              Yes          No          No              No        One year   \n",
       "\n",
       "  PaperlessBilling     PaymentMethod  MonthlyCharges TotalCharges Churn  \n",
       "0              Yes  Electronic check           29.85        29.85    No  \n",
       "1               No      Mailed check           56.95       1889.5    No  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "yjmi7pa4u8rN",
    "outputId": "9c9c1174-a99d-41dd-bc82-6712718778b5",
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 21 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   customerID        7043 non-null   object \n",
      " 1   gender            7043 non-null   object \n",
      " 2   SeniorCitizen     7043 non-null   int64  \n",
      " 3   Partner           7043 non-null   object \n",
      " 4   Dependents        7043 non-null   object \n",
      " 5   tenure            7043 non-null   int64  \n",
      " 6   PhoneService      7043 non-null   object \n",
      " 7   MultipleLines     7043 non-null   object \n",
      " 8   InternetService   7043 non-null   object \n",
      " 9   OnlineSecurity    7043 non-null   object \n",
      " 10  OnlineBackup      7043 non-null   object \n",
      " 11  DeviceProtection  7043 non-null   object \n",
      " 12  TechSupport       7043 non-null   object \n",
      " 13  StreamingTV       7043 non-null   object \n",
      " 14  StreamingMovies   7043 non-null   object \n",
      " 15  Contract          7043 non-null   object \n",
      " 16  PaperlessBilling  7043 non-null   object \n",
      " 17  PaymentMethod     7043 non-null   object \n",
      " 18  MonthlyCharges    7043 non-null   float64\n",
      " 19  TotalCharges      7043 non-null   object \n",
      " 20  Churn             7043 non-null   object \n",
      "dtypes: float64(1), int64(2), object(18)\n",
      "memory usage: 1.1+ MB\n"
     ]
    }
   ],
   "source": [
    "# check data information\n",
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "fBGk-iK-ciF9",
    "tags": []
   },
   "source": [
    "Total charges column data type should be of datatype `float`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Transform Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "id": "NXWn85v6vx3a",
    "tags": [
     "block:transform_data",
     "prev:load_data"
    ]
   },
   "outputs": [],
   "source": [
    "# remove rows with spaces\n",
    "data = data[data['TotalCharges'] !=' '].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "nUBk6ua-cyoV",
    "outputId": "e450fa4c-54de-46b1-c297-4385f0e5b139",
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7032, 21)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 11 rows removed\n",
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "id": "6_3BDLuv6iZ3",
    "tags": []
   },
   "outputs": [],
   "source": [
    "data['TotalCharges'] = data['TotalCharges'].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "id": "aZKrWUXYjqg7",
    "tags": []
   },
   "outputs": [],
   "source": [
    "# check for data cardinality\n",
    "lis3=[]\n",
    "for i in data:\n",
    "    lis3.append(data[str(i)].nunique())\n",
    "\n",
    "cardinal=pd.DataFrame(zip(data.columns, lis3), columns=['Features', 'cardinality'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 708
    },
    "id": "g1U3BMAslrXy",
    "outputId": "30bef1ee-4e72-4ab2-d72d-36c670dd2bc0",
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Features</th>\n",
       "      <th>cardinality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>customerID</td>\n",
       "      <td>7032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gender</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SeniorCitizen</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Partner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Dependents</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>tenure</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>PhoneService</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>MultipleLines</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>InternetService</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>OnlineSecurity</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>OnlineBackup</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>DeviceProtection</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>TechSupport</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>StreamingTV</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>StreamingMovies</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Contract</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>PaperlessBilling</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>PaymentMethod</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>MonthlyCharges</td>\n",
       "      <td>1584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>TotalCharges</td>\n",
       "      <td>6530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Churn</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Features  cardinality\n",
       "0         customerID         7032\n",
       "1             gender            2\n",
       "2      SeniorCitizen            2\n",
       "3            Partner            2\n",
       "4         Dependents            2\n",
       "5             tenure           72\n",
       "6       PhoneService            2\n",
       "7      MultipleLines            3\n",
       "8    InternetService            3\n",
       "9     OnlineSecurity            3\n",
       "10      OnlineBackup            3\n",
       "11  DeviceProtection            3\n",
       "12       TechSupport            3\n",
       "13       StreamingTV            3\n",
       "14   StreamingMovies            3\n",
       "15          Contract            3\n",
       "16  PaperlessBilling            2\n",
       "17     PaymentMethod            4\n",
       "18    MonthlyCharges         1584\n",
       "19      TotalCharges         6530\n",
       "20             Churn            2"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cardinal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "id": "ZWFEooyXm4VG",
    "tags": []
   },
   "outputs": [],
   "source": [
    "# get columns with unique values less than 5 for discrete variable EDA\n",
    "cols=[]\n",
    "for i in data:\n",
    "  if data[str(i)].nunique() < 5:\n",
    "    cols.append(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "gDKVRLcAmivQ",
    "outputId": "d0bf82ca-ebe0-42fe-f43c-6fac25ad280d",
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hv7+6ZqPXsTkrcat6aXP06KOPMn78+NJl9Jr2nk9EzM/Mlvb6N/OquQOA6cDDEbGgbjsPOD4iJgEJLAX+DCAzF0fEXKqLENYCp2bmuvoJnAbcAQwG5nQWQpKk/qWZV83dS7U309btnSxzEXBRO+23d7acJKn/8hY/kqSiDCJJ2gQ063x9X9uQ5+G95qQBwAtvOlf6wpvhw4ezevVqtttuO6rrvPqnzGT16tUMHz68R8sZRJJU2JgxY1i+fDmbw/9ADh8+nDFjxvRoGYNIkgobOnQou+22W+kyivEckSSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpqKYFUUTsHBH3RMQjEbE4Is6s27eNiDsj4vH6cZu6PSLi8ohYEhELI2LfhnXNqPs/HhEzmlWzJKnvNXOPaC1wdmbuCewPnBoRewLnAHdn5jjg7noa4HBgXD3MBL4JVXABFwDvAyYDF7SGlySp/2taEGXm05n583r8JeBRYCdgGnB13e1q4Kh6fBpwTVbuB94ZETsAhwJ3Zubzmflr4E7gsGbVLUnqW31yjigixgL7AD8DRmfm0/WsZ4DR9fhOwFMNiy2v2zpqb7uNmRExLyLmrVy5snefgCSpaZoeRBGxFXAjcFZm/qZxXmYmkL2xncycnZktmdkyatSo3lilJKkPNDWIImIoVQhdm5k31c3P1ofcqB+fq9tXADs3LD6mbuuoXZK0GWjmVXMBXAU8mplfb5h1K9B65dsM4JaG9pPrq+f2B16sD+HdAXw4IrapL1L4cN0mSdoMDGniug8ApgMPR8SCuu084O+AuRHxaeBXwDH1vNuBqcAS4BXgUwCZ+XxEfAl4sO53YWY+38S6JUl9qGlBlJn3AtHB7IPb6Z/AqR2saw4wp/eqkyRtKryzgiSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkopqWhBFxJyIeC4iFjW0zYqIFRGxoB6mNsw7NyKWRMQvIuLQhvbD6rYlEXFOs+qVJJXRrSCKiLu709bGt4HD2mm/JDMn1cPt9br2BI4DJtTL/GNEDI6IwcA3gMOBPYHj676SpM3EkM5mRsRw4G3AyIjYBoh61tuBnTpbNjN/HBFju1nHNOD6zHwN+GVELAEm1/OWZOaTdT3X130f6eZ6JUmbuK72iP4MmA+8p35sHW4B/mEDt3laRCysD91tU7ftBDzV0Gd53dZRuyRpM9FpEGXmZZm5G/DZzNw9M3erh70zc0OC6JvAHsAk4GngaxuwjnZFxMyImBcR81auXNlbq5UkNVmnh+ZaZeYVEfEBYGzjMpl5TU82lpnPto5HxD8D/1ZPrgB2bug6pm6jk/a2654NzAZoaWnJntQlSSqnW0EUEd+h2pNZAKyrmxPoURBFxA6Z+XQ9+TGg9Yq6W4HvRsTXgR2BccADVOekxkXEblQBdBxwQk+2KUnatHUriIAWYM/M7PaeRkRcB0yhutBhOXABMCUiJlGF2FKqc1Bk5uKImEt1EcJa4NTMXFev5zTgDmAwMCczF3e3BknSpq+7QbQIeBfVeZ1uyczj22m+qpP+FwEXtdN+O3B7d7crSepfuhtEI4FHIuIB4LXWxsw8silVSZIGjO4G0axmFiFJGri6e9Xcj5pdiCRpYOruVXMvUV1gALAFMBR4OTPf3qzCJEkDQ3f3iLZuHY+IoLrNzv7NKkqSNHD0+O7bWflX4NCu+kqS1JXuHpo7umFyENX/Fb3alIokSQNKd6+a+2jD+Fqqf0ad1uvVSJIGnO6eI/pUswuRJA1M3f1ivDERcXP9javPRcSNETGm2cVJkjZ/3b1Y4VtUNybdsR5uq9skSdoo3Q2iUZn5rcxcWw/fBkY1sS5J0gDR3SBaHREnRcTgejgJWN3MwiRJA0N3g+gU4BjgGao7cH8c+GSTapIkDSDdvXz7QmBGZv4aICK2BS6mCihJkjZYd/eIJraGEEBmPg/s05ySJEkDSXeDaFBEbNM6Ue8RdXdvSpKkDnU3TL4G3BcRN9TTn6Cdb1OVJKmnuntnhWsiYh5wUN10dGY+0ryyJEkDRbcPr9XBY/hIknpVj78GQpKk3mQQSZKKMogkSUUZRJKkogwiSVJRBpEkqSiDSJJUlEEkSSrKIJIkFWUQSZKKMogkSUUZRJKkovxOIUkD3rIL31u6hE3WLl94uOnbcI9IklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkopqWhBFxJyIeC4iFjW0bRsRd0bE4/XjNnV7RMTlEbEkIhZGxL4Ny8yo+z8eETOaVa8kqYxm7hF9GzisTds5wN2ZOQ64u54GOBwYVw8zgW9CFVzABcD7gMnABa3hJUnaPDQtiDLzx8DzbZqnAVfX41cDRzW0X5OV+4F3RsQOwKHAnZn5fGb+GriTt4abJKkf6+tzRKMz8+l6/BlgdD2+E/BUQ7/ldVtH7ZKkzUSxixUyM4HsrfVFxMyImBcR81auXNlbq5UkNVlfB9Gz9SE36sfn6vYVwM4N/cbUbR21v0Vmzs7MlsxsGTVqVK8XLklqjr4OoluB1ivfZgC3NLSfXF89tz/wYn0I7w7gwxGxTX2RwofrNknSZmJIs1YcEdcBU4CREbGc6uq3vwPmRsSngV8Bx9TdbwemAkuAV4BPAWTm8xHxJeDBut+Fmdn2AghJUj/WtCDKzOM7mHVwO30TOLWD9cwB5vRiaZKkTYh3VpAkFWUQSZKKMogkSUUZRJKkogwiSVJRBpEkqSiDSJJUlEEkSSrKIJIkFWUQSZKKMogkSUUZRJKkogwiSVJRBpEkqSiDSJJUlEEkSSrKIJIkFWUQSZKKMogkSUUZRJKkogwiSVJRBpEkqSiDSJJUlEEkSSrKIJIkFWUQSZKKMogkSUUZRJKkogwiSVJRBpEkqSiDSJJUlEEkSSrKIJIkFWUQSZKKMogkSUUZRJKkooaULkD917IL31u6hE3WLl94uHQJUr/hHpEkqSiDSJJUlEEkSSrKIJIkFWUQSZKKMogkSUUZRJKkogwiSVJRBpEkqSiDSJJUlEEkSSrKIJIkFWUQSZKKMogkSUUZRJKkogwiSVJRBpEkqagiQRQRSyPi4YhYEBHz6rZtI+LOiHi8ftymbo+IuDwilkTEwojYt0TNkqTmKLlH9KHMnJSZLfX0OcDdmTkOuLueBjgcGFcPM4Fv9nmlkqSm2ZQOzU0Drq7HrwaOami/Jiv3A++MiB0K1CdJaoJSQZTAf0TE/IiYWbeNzsyn6/FngNH1+E7AUw3LLq/b3iQiZkbEvIiYt3LlymbVLUnqZUMKbfeDmbkiIrYH7oyIxxpnZmZGRPZkhZk5G5gN0NLS0qNlJUnlFNkjyswV9eNzwM3AZODZ1kNu9eNzdfcVwM4Ni4+p2yRJm4E+D6KI2DIitm4dBz4MLAJuBWbU3WYAt9TjtwIn11fP7Q+82HAIT5LUz5U4NDcauDkiWrf/3cz8QUQ8CMyNiE8DvwKOqfvfDkwFlgCvAJ/q+5IlSc3S50GUmU8Ce7fTvho4uJ32BE7tg9IkSQVsSpdvS5IGIINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKsogkiQVZRBJkorqN0EUEYdFxC8iYklEnFO6HklS7+gXQRQRg4FvAIcDewLHR8SeZauSJPWGfhFEwGRgSWY+mZm/A64HphWuSZLUC/pLEO0EPNUwvbxukyT1c0NKF9BbImImMLOeXBMRvyhZz0CwK4wEVpWuY5N0QZSuQD3gz3Ineu9nedeOZvSXIFoB7NwwPaZuWy8zZwOz+7KogS4i5mVmS+k6pI3lz3JZ/eXQ3IPAuIjYLSK2AI4Dbi1ckySpF/SLPaLMXBsRpwF3AIOBOZm5uHBZkqRe0C+CCCAzbwduL12H3sRDodpc+LNcUGRm6RokSQNYfzlHJEnaTBlE6lBU7o2IwxvaPhERPyhZl7ShIiIj4msN05+NiFkFSxIGkTqR1XHbzwBfj4jhEbEV8GXg1LKVSRvsNeDoiBhZuhD9nkGkTmXmIuA24K+BLwD/AvxNRDwQEQ9FxDSAiJhQty2IiIURMa5g2VJH1lJdmPAXbWdExNiI+GH983t3ROzS9+UNTF6soC5FxJbAz4HfAf8GLM7Mf4mIdwIPAPsAfwfcn5nX1v/rNTgzf1uqZqk9EbEG2BFYCOwN/CmwVWbOiojbgP+bmVdHxCnAkZl5VLlqBw6DSN0SERcCa4BjgOFUf1kCbAscShVGfwNcA9yUmY+XqFPqTESsycyt6p/n14Hf8vsgWgXskJmvR8RQ4OnM9BBeH/DQnLrrjXoI4I8zc1I97JKZj2bmd4EjqX6xb4+Ig0oWK3XhUuDTwJaF6xAGkXruDuD0iAiAiNinftwdeDIzLwduASaWK1HqXGY+D8ylCqNW/0V1+zCAE4Gf9HVdA5VBpJ76EjAUWBgRi+tpqA7ZLYqIBcBeVIfopE3Z16juut3qdOBTEbEQmA6cWaSqAchzRJKkotwjkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkdQkEbGuvvfeooi4ISLe1oNlJ0XE1GbWJ20qDCKpeX5b331iL6r79H2mOwtFxBBgEtBrQRQRg3trXVJv6zdfFS71cz8BJkbER4HPA1sAq4ETM/PZ+jtx9gB2B5YBBwAjIuKDwFeA8cAu9fxdgEvru1gQEScBZ9Tr/Bnw55m5rr7B5z8Bh1B9dce9ffRcpR5xj0hqsnoP53DgYaow2D8z9wGuBz7X0HVP4JDMPJ7qKze+V+9Rfa+e/x6qG8xOBi6IiKERMR44FjggMycB66huTwPVfdR+lpl7Z6YhpE2We0RS84yob3kE1R7RVcAfAt+LiB2o9mB+2dD/1i6+OuPfM/M14LWIeA4YDRwM7Ac8WN/+bwTwXN1/HXBjLz0XqWkMIql5flvvpawXEVcAX8/MWyNiCjCrYfbLXazvtYbxdVS/vwFcnZnnttP/1cxc18OapT7noTmpb70DWFGPz+ik30vA1t1Y393AxyNie4CI2DYidt24EqW+ZRBJfWsWcENEzAdWddLvHmDP+vLvYzvqlJmPUF388B/1XaPvBHboxXqlpvPu25KkotwjkiQVZRBJkooyiCRJRRlEkqSiDCJJUlEGkSSpKINIklSUQSRJKur/A1zJ9ahzEnk8AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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pKoNIklSVQSRJ/VxmstNOO/GLX/xiYduPfvQjdtttt17Zvt8jkqQVzIMnv7VH17fJCXcudnpEcOaZZ7LPPvvwnve8hwULFnD88cfzy1/+skfr6IpBJEli6623Zs899+QrX/kKzz77LB/96Ec55ZRTmDFjBvPnz2fy5MlMmDCBmTNncsghh/Diiy/y8ssvc8kllzB69Ojl2rZBJEkC4MQTT2S77bZjlVVW4QMf+ADjx4/nnHPO4emnn2b77bfnve99L2eeeSZHHXUUBx54IC+++CIvvfTScm/XIJIkAbDaaqux3377sfrqq3PxxRfzs5/9jFNPPRWA559/ngcffJB3vOMdnHLKKcyePZsPf/jDy300BAaRJKnFgAEDGDBgAJnJJZdcwpvf/OZXTd9iiy3YYYcd+PnPf84ee+zBd7/7XcaPH79821yupSVJfdKuu+7K6aefTmYCcNtttwFw3333sdlmm3HkkUcyYcIEpk+fvtzbMogkSa/xhS98gfnz57PNNtuw1VZb8YUvfAGAiy++mK233poxY8YwY8YMDj54+a8UHh1p15eMHTs2p02bttzreftnz+uBavquGpeql/qiu+++my222KJ2GT2ms+cTEbdm5tjO5veISJJUlUEkSarKIJIkVWUQSdIKoK98Xr8sz6NtQRQRQyPi5oi4IyJmRsRJpX1URNwUEbMi4ocRsUppH1LGZ5XpI1vWdVxp/2NE7NqumiWphqFDhzJ37tyVPowyk7lz5zJ06NClWq6dX2h9ARifmfMiYjBwfUT8AvgM8I3MnBIRZwIfB84oP5/KzDdGxP7AV4D9ImJLYH9gK2BD4OqIeFNmLv91JSRpBTBixAhmz57NnDlzapey3IYOHcqIESOWapm2BVE20T6vjA4ujwTGAweU9nOByTRBNKEMA/wY+HZERGmfkpkvAH+OiFnA9sAN7apdknrT4MGDGTVqVO0yqmnrZ0QRMTAibgceB64C/gQ8nZkLyiyzgY3K8EbAQwBl+jPAuq3tnSwjSVrJtTWIMvOlzBwDjKA5inlLu7YVEZMiYlpETOsLh7eS1F/0Sq+5zHwauBZ4B7BWRHScEhwBPFyGHwY2BijTXw/MbW3vZJnWbZyVmWMzc+zw4cPb8TQkSW3Qzl5zwyNirTK8KvA+4G6aQNq7zDYR+GkZnlrGKdN/XT5nmgrsX3rVjQJGAze3q25JUu9qZ6+5DYBzI2IgTeBdnJmXR8RdwJSI+BJwG3B2mf9s4PzSGeFJmp5yZObMiLgYuAtYABxmjzlJ6jva2WtuOrBtJ+330XxetGj788A+XazrFOCUnq5RklSfV1aQJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFXVtiCKiI0j4tqIuCsiZkbEUaV9ckQ8HBG3l8ceLcscFxGzIuKPEbFrS/tupW1WRBzbrpolSb1vUBvXvQA4JjP/EBFrALdGxFVl2jcy89TWmSNiS2B/YCtgQ+DqiHhTmfwd4H3AbOCWiJiamXe1sXZJUi9pWxBl5iPAI2X4bxFxN7DRYhaZAEzJzBeAP0fELGD7Mm1WZt4HEBFTyrwGkST1Ab3yGVFEjAS2BW4qTYdHxPSIOCci1i5tGwEPtSw2u7R11S5J6gPaHkQRsTpwCXB0Zv4VOAPYHBhDc8T0tR7azqSImBYR0+bMmdMTq5Qk9YK2BlFEDKYJoQsz81KAzHwsM1/KzJeB/+KV028PAxu3LD6itHXV/iqZeVZmjs3MscOHD+/5JyNJaot29poL4Gzg7sz8ekv7Bi2zfQiYUYanAvtHxJCIGAWMBm4GbgFGR8SoiFiFpkPD1HbVLUnqXe3sNfcu4CDgzoi4vbQdD3wkIsYACdwPfBIgM2dGxMU0nRAWAIdl5ksAEXE4cCUwEDgnM2e2sW5JUi9qZ6+564HoZNIVi1nmFOCUTtqvWNxykqSVl1dWkCRVZRBJkqoyiCRJVRlEkqSqDCJJUlUGkSSpKoNIklSVQSRJqsogkiRVZRBJkqoyiCRJVRlEkqSqDCJJUlUGkSSpKoNIklSVQSRJqsogkiRVZRBJkqoyiCRJVRlEkqSqDCJJUlUGkSSpKoNIklSVQSRJqsogkiRVZRBJkqoyiCRJVRlEkqSqDCJJUlUGkSSpKoNIklSVQSRJqsogkiRVZRBJkqoyiCRJVRlEkqSqDCJJUlUGkSSpKoNIklSVQSRJqsogkiRVZRBJkqpqWxBFxMYRcW1E3BURMyPiqNK+TkRcFRH3lp9rl/aIiNMiYlZETI+I7VrWNbHMf29ETGxXzZKk3tfOI6IFwDGZuSWwI3BYRGwJHAtck5mjgWvKOMDuwOjymAScAU1wAScCOwDbAyd2hJckaeXXtiDKzEcy8w9l+G/A3cBGwATg3DLbucBeZXgCcF42bgTWiogNgF2BqzLzycx8CrgK2K1ddUuSelevfEYUESOBbYGbgPUz85Ey6VFg/TK8EfBQy2KzS1tX7YtuY1JETIuIaXPmzOnZJyBJapu2B1FErA5cAhydmX9tnZaZCWRPbCczz8rMsZk5dvjw4T2xSklSL2hrEEXEYJoQujAzLy3Nj5VTbpSfj5f2h4GNWxYfUdq6apck9QHt7DUXwNnA3Zn59ZZJU4GOnm8TgZ+2tB9ces/tCDxTTuFdCewSEWuXTgq7lDZJUh8wqI3rfhdwEHBnRNxe2o4HvgxcHBEfBx4A9i3TrgD2AGYBzwGHAGTmkxHxReCWMt/JmflkG+uWJPWitgVRZl4PRBeTd+5k/gQO62Jd5wDn9Fx1kqQVhVdWkCRVZRBJkqoyiCRJVRlEkqSqDCJJUlXdCqKIuKY7bZIkLa3Fdt+OiKHA64Bh5cukHd2x16ST671JkrS0lvQ9ok8CRwMbArfyShD9Ffh2+8qSJPUXiw2izPwW8K2IOCIzT++lmiRJ/Ui3rqyQmadHxDuBka3LZOZ5bapLktRPdCuIIuJ8YHPgduCl0pyAQSRJWi7dvdbcWGDLcj04SZJ6THe/RzQDeEM7C5Ek9U/dPSIaBtwVETcDL3Q0ZuYH21KVJKnf6G4QTW5nEZKk/qu7veZ+2+5CJEn9U3d7zf2NppccwCrAYODZzFyzXYVJkvqH7h4RrdExHBEBTAB2bFdRknrW2z/rNy0W59avHly7hH5tqa++nY2fALv2fDmSpP6mu6fmPtwyOoDme0XPt6UiSVK/0t1ec3u2DC8A7qc5PSdJ0nLp7mdEh7S7EElS/9TdG+ONiIjLIuLx8rgkIka0uzhJUt/X3c4K3wem0tyXaEPgZ6VNkqTl0t0gGp6Z38/MBeXxA2B4G+uSJPUT3Q2iuRHx0YgYWB4fBea2szBJUv/Q3SA6FNgXeBR4BNgb+FibapIk9SPd7b59MjAxM58CiIh1gFNpAkqSpGXW3SOibTpCCCAznwS2bU9JkqT+pLtBNCAi1u4YKUdE3T2akiSpS90Nk68BN0TEj8r4PsAp7SlJktSfdPfKCudFxDRgfGn6cGbe1b6yJEn9RbdPr5XgMXwkST1qqW8DIUlSTzKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqysv0aJk9ePJba5ewwtrkhDtrlyCtNNp2RBQR55Tbis9oaZscEQ9HxO3lsUfLtOMiYlZE/DEidm1p3620zYqIY9tVrySpjnaemvsBsFsn7d/IzDHlcQVARGwJ7A9sVZb5z46b8AHfAXYHtgQ+UuaVJPURbTs1l5nXRcTIbs4+AZiSmS8Af46IWcD2ZdqszLwPICKmlHm91JAk9RE1OiscHhHTy6m7jltLbAQ81DLP7NLWVftrRMSkiJgWEdPmzJnTjrolSW3Q20F0BrA5MIbmluNf66kVZ+ZZmTk2M8cOHz68p1YrSWqzXu01l5mPdQxHxH8Bl5fRh4GNW2YdUdpYTLskqQ/o1SOiiNigZfRDQEePuqnA/hExJCJGAaOBm4FbgNERMSoiVqHp0DC1N2uWJLVX246IIuIiYBwwLCJmAycC4yJiDJDA/cAnATJzZkRcTNMJYQFwWGa+VNZzOHAlMBA4JzNntqtmSVLva2evuY900nz2YuY/hU5uP166eF/Rg6VJklYgXuJHklSVQSRJqsogkiRVZRBJkqoyiCRJVRlEkqSqDCJJUlUGkSSpKoNIklSVQSRJqsogkiRVZRBJkqoyiCRJVRlEkqSqDCJJUlUGkSSpKoNIklSVQSRJqsogkiRVZRBJkqoyiCRJVRlEkqSqDCJJUlUGkSSpKoNIklSVQSRJqsogkiRVZRBJkqoyiCRJVRlEkqSqDCJJUlUGkSSpKoNIklSVQSRJqsogkiRVZRBJkqoyiCRJVRlEkqSqDCJJUlUGkSSpKoNIklRV24IoIs6JiMcjYkZL2zoRcVVE3Ft+rl3aIyJOi4hZETE9IrZrWWZimf/eiJjYrnolSXW084joB8Bui7QdC1yTmaOBa8o4wO7A6PKYBJwBTXABJwI7ANsDJ3aElySpb2hbEGXmdcCTizRPAM4tw+cCe7W0n5eNG4G1ImIDYFfgqsx8MjOfAq7iteEmSVqJ9fZnROtn5iNl+FFg/TK8EfBQy3yzS1tX7ZKkPqJaZ4XMTCB7an0RMSkipkXEtDlz5vTUaiVJbdbbQfRYOeVG+fl4aX8Y2LhlvhGlrav218jMszJzbGaOHT58eI8XLklqj94OoqlAR8+3icBPW9oPLr3ndgSeKafwrgR2iYi1SyeFXUqbJKmPGNSuFUfERcA4YFhEzKbp/fZl4OKI+DjwALBvmf0KYA9gFvAccAhAZj4ZEV8EbinznZyZi3aAkCStxNoWRJn5kS4m7dzJvAkc1sV6zgHO6cHSJEkrEK+sIEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqqkoQRcT9EXFnRNweEdNK2zoRcVVE3Ft+rl3aIyJOi4hZETE9IrarUbMkqT1qHhG9JzPHZObYMn4scE1mjgauKeMAuwOjy2MScEavVypJapsV6dTcBODcMnwusFdL+3nZuBFYKyI2qFCfJKkNagVRAr+KiFsjYlJpWz8zHynDjwLrl+GNgIdalp1d2iRJfcCgStvdKTMfjoj1gKsi4p7WiZmZEZFLs8ISaJMANtlkk56rVJLUVlWOiDLz4fLzceAyYHvgsY5TbuXn42X2h4GNWxYfUdoWXedZmTk2M8cOHz68neVLknpQrwdRRKwWEWt0DAO7ADOAqcDEMttE4KdleCpwcOk9tyPwTMspPEnSSq7Gqbn1gcsiomP7/52Zv4yIW4CLI+LjwAPAvmX+K4A9gFnAc8AhvV+yJKldej2IMvM+4G2dtM8Fdu6kPYHDeqE0SVIFK1L3bUlSP2QQSZKqMogkSVUZRJKkqgwiSVJVBpEkqSqDSJJUlUEkSarKIJIkVWUQSZKqMogkSVUZRJKkqmrdGE+SVhgPnvzW2iWssDY54c62b8MjIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqaqUJoojYLSL+GBGzIuLY2vVIknrGShFEETEQ+A6wO7Al8JGI2LJuVZKknrBSBBGwPTArM+/LzBeBKcCEyjVJknrAyhJEGwEPtYzPLm2SpJXcoNoF9JSImARMKqPzIuKPNevpDzaFYcATtetYIZ0YtSvQUvC1vBg991retKsJK0sQPQxs3DI+orQtlJlnAWf1ZlH9XURMy8yxteuQlpev5bpWllNztwCjI2JURKwC7A9MrVyTJKkHrBRHRJm5ICIOB64EBgLnZObMymVJknrAShFEAJl5BXBF7Tr0Kp4KVV/ha7miyMzaNUiS+rGV5TMiSVIfZRBpiSIiI+JrLeP/GhGTK5YkLZVoXB8Ru7e07RMRv6xZlxoGkbrjBeDDETGsdiHSssjmM4hPAV+PiKERsTrwH8BhdSsTGETqngU0H+Z+etEJETEyIn4dEdMj4pqI2KT3y5OWLDNnAD8DPgecAFwA/HtE3BwRt0XEBICI2Kq03V5e16Mrlt0v2FlBSxQR84ANgenA24BPAKtn5uSI+Bnw48w8NyIOBT6YmXvVq1bqWkSsBvwBeBG4HJiZmRdExFrAzcC2wJeBGzPzwvK9xYGZ+fdaNfcHBpGWKCLmZebqEXEyMB/4O68E0RPABpk5PyIGA49kpqfwtMIqr+N5wL7AUJojfoB1gF1pwujfgfOASzPz3hp19ieemtPS+CbwcWC1ynVIy+Pl8gjg/2bmmPLYJDPvzsz/Bj5I8w/XFRExvmax/YFBpG7LzCeBi2nCqMP/0FxyCeBA4He9XZe0jK4EjoiIAIiIbcvPzYD7MvM04KfANvVK7B8MIi2tr9FcqbjDEcAhETEdOAg4qkpV0tL7IjAYmB4RM8s4NKfsZkTE7cDWNKfo1EZ+RiRJqsojIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEndFBEvleuPzYyIOyLimIio9jcUEfcv64VoI2KviNiyp2uSloVBJHXf38s38LcC3gfsDpxYuaZltRdgEGmFYBBJyyAzHwcmAYeXe90MjIivRsQt5YrNnwSIiHERcV1E/Dwi/hgRZ3YcRUXELhFxQ0T8ISJ+VG5N0HGkc1JpvzMi3lLa142IX5Ujsu/RXKKGMu2jLVeM/m5EDCzt8yLilHIEd2NErB8R76S5hM1Xy/ybR8SREXFXqX1Kr+5M9XsGkbSMMvM+YCCwHs1lj57JzH8A/gH4RESMKrNuT3MFii2BzXnl3k6fB96bmdsB04DPtKz+idJ+BvCvpe1E4PpyRHYZsAlARGwB7Ae8KzPHAC/RXG4JmusC3piZbwOuAz6Rmf8DTAU+W47w/gQcC2ybmdvQ3LdH6jWDahcg9RG7ANtExN5l/PXAaJrbDdxcQouIuAjYCXieJph+Xy51tgpwQ8v6Li0/bwU+XIb/T8dwZv48Ip4q7TsDbwduKetaFXi8TOu43UHHut7XRf3TgQsj4ifAT7r/tKXlZxBJy6hcHPMlmjf9AI7IzCsXmWccsOh1tLLMf1VmfqSL1b9Qfr7Ekv9OAzg3M4/rZNr8fOU6Xotb1/tpgm5PmpvFvTUzF3Qxr9SjPDUnLYOIGA6cCXy7vNFfCfxzuScTEfGmchM2gO0jYlT5bGg/4HrgRuBdEfHGMv9qEfGmJWz2OuCAMv/uwNql/Rpg74hYr0xbJyI2XcK6/gasUeYfAGycmdfS3L309cDq3dkPUk/wiEjqvlXLFZkH09xM7Xzg62Xa94CRwB/KbQXm0PRMA7gF+DbwRuBa4LLMfDkiPgZcFBFDynyfB/53Mds/qcw/k+b2Gw8CZOZdEfF54FclVOYDhwEPLGZdU4D/iogjaW7jcXZEvJ7m6Oq0zHx6STtD6ilefVtqo3Jq7l8z8wOVS5FWWJ6akyRV5RGRJKkqj4gkSVUZRJKkqgwiSVJVBpEkqSqDSJJUlUEkSarq/wMmZU4N3aRdLAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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45ppr1rR98pOf5KabbgJg8uTJ7LPPPhVdp4PIzMze46yzzuKVV15Zc//KK6/k2muvZdCgQdxwww1cfvnlFV1f1Q5WMDOzdZPj0i5Lly5dM7zNNtvw1ltvrbm//fbbc99991Vt3e4RmZlZVg4iMzPLykFkZmZZOYjMzCwrB5GZmWXlIDIzs6wcRGZmHVxEsPfee/OHP/xhTdstt9zCgQe2zsWw/TsiM7MNzPwLP1bR5fU976m1jpfE1Vdfzec//3k++9nPsnLlSs455xz++Mc/VrSOpjiIzMyM3XbbjcMOO4wf/ehHvPnmmxx//PGMHz+emTNnsmLFCsaNG8eIESOYNWsWJ554Iu+88w6rV69mypQpDBgwYL3W7SAyMzMAzj//fPbYYw822mgjDj30UIYPH87EiRN57bXXGDp0KPvttx9XX301Z5xxBscddxzvvPMOq1atWu/1OojMzAyATTbZhC984Qtsuumm3Hzzzdx5551cfPHFACxbtoz58+ez1157MX78eOrq6jjqqKPWuzcEDiIzMyvRqVMnOnXqREQwZcoUdt555/eM32WXXfjEJz7B73//ew4++GB+/vOfM3z48PVb53rNbWZm7dIBBxzAlVdeSXHxbHjyyScBmDt3LjvssAOnn346I0aMYMaMGeu9LgeRmZm9z7nnnsuKFSsYNGgQAwcO5NxzzwXg5ptvZrfddmPw4MHMnDmT0aPX/0zhqk+79qampiZqa2vLmnbI1ydVuZrqynHKeDOrnKeffppddtkldxkV09jjkTQtImoam949IjMzy8pBZGZmWTmIzMwsKweRmdkGoL3sr1+Xx+EgMjPLrHv37ixZsqTNh1FEsGTJErp3796i+fyDVjOzzHr37k1dXR2LFy/OXcp66969O717927RPA4iM7PMunbtSv/+/XOXkY03zZmZWVYOIjMzy8pBZGZmWTmIzMwsKweRmZll5SAyM7OsqhZEkiZKelnSzJK230ianm7zJE1P7f0kvV0y7uqSeYZIekrSHElXSFK1ajYzs9ZXzd8RXQf8FFhzjYWI+EL9sKRLgNdLpn8+IgY3spyrgP8CHgPuAg4E/lD5cs3MLIeq9Ygi4gHg1cbGpV7NMcCNa1uGpG2BzSPi0SjOfTEJOKLCpZqZWUa59hHtA7wUEc+VtPWX9KSk+yXtk9p6AXUl09SlNjMzaydyneLnWN7bG1oE9I2IJZKGALdLGtjShUoaC4wF6Nu3b0UKNTOz6mr1HpGkLsBRwG/q2yJieUQsScPTgOeBnYCFQOnZ83qntkZFxISIqImImp49e1ajfDMzq7Acm+b2A56JiDWb3CT1lNQ5De8ADADmRsQi4A1Je6b9SqOB32ao2czMqqSah2/fCDwC7CypTtKX0qiRvP8ghU8DM9Lh3P8LnBwR9Qc6fAX4JTCHoqfkI+bMzNqRqu0jiohjm2g/oZG2KcCUJqavBXaraHFmZrbB8PWIrN0b8vVJzU+0gZr249G5SzCrOp/ix8zMsnIQmZlZVg4iMzPLykFkZmZZOYjMzCwrB5GZmWXlIDIzs6wcRGZmlpWDyMzMsnIQmZlZVg4iMzPLykFkZmZZOYjMzCwrB5GZmWXlIDIzs6wcRGZmlpWDyMzMsnIQmZlZVg4iMzPLykFkZmZZOYjMzCwrB5GZmWXlIDIzs6wcRGZmlpWDyMzMsnIQmZlZVg4iMzPLykFkZmZZOYjMzCwrB5GZmWXlIDIzs6wcRGZmllXVgkjSREkvS5pZ0jZO0kJJ09Pt4JJxZ0uaI+lZSQeUtB+Y2uZI+la16jUzszyq2SO6DjiwkfZLI2Jwut0FIGlXYCQwMM3zP5I6S+oM/Aw4CNgVODZNa2Zm7USXai04Ih6Q1K/MyUcAN0XEcuAFSXOAoWncnIiYCyDppjTt7ErXa2ZmeeTYR3SqpBlp092Wqa0XsKBkmrrU1lR7oySNlVQrqXbx4sWVrtvMzKqgtYPoKmBHYDCwCLikkguPiAkRURMRNT179qzkos3MrEqqtmmuMRHxUv2wpF8Av0t3FwJ9SibtndpYS7uZmbUDrdojkrRtyd0jgfoj6u4ARkrqJqk/MAB4HPgbMEBSf0kbURzQcEdr1mxmZtVVtR6RpBuBYUAPSXXA+cAwSYOBAOYBXwaIiFmSbqY4CGElcEpErErLORW4G+gMTIyIWdWq2czMWl81j5o7tpHma9Yy/XhgfCPtdwF3VbA0MzPbgPjMCmZmllWrHqxg1TH/wo/lLmG99D3vqdwlmFlG7hGZmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyy8g9azazNGvL1SblLWC/Tfjw6dwkbBPeIzMwsKweRmZll5SAyM7OsHERmZpaVg8jMzLJyEJmZWVYOIjMzy8pBZGZmWTmIzMwsKweRmZll5SAyM7OsHERmZpaVg8jMzLJyEJmZWVYOIjMzy8pBZGZmWTmIzMwsKweRmZll5SAyM7OsHERmZpaVg8jMzLKqWhBJmijpZUkzS9p+LOkZSTMk3SZpi9TeT9Lbkqan29Ul8wyR9JSkOZKukKRq1WxmZq2vmj2i64ADG7RNBXaLiEHA/wFnl4x7PiIGp9vJJe1XAf8FDEi3hss0M7M2rGpBFBEPAK82aPtTRKxMdx8Feq9tGZK2BTaPiEcjIoBJwBFVKNfMzDLJuY/oJOAPJff7S3pS0v2S9kltvYC6kmnqUpuZmbUTXXKsVNK3gZXA5NS0COgbEUskDQFulzRwHZY7FhgL0Ldv30qVa2ZmVdTqPSJJJwCHAselzW1ExPKIWJKGpwHPAzsBC3nv5rveqa1RETEhImoioqZnz55VegRmZlZJrRpEkg4EvgEcHhFvlbT3lNQ5De9AcVDC3IhYBLwhac90tNxo4LetWbOZmVVX1TbNSboRGAb0kFQHnE9xlFw3YGo6CvvRdITcp4ELJa0AVgMnR0T9gQ5foTgCb2OKfUql+5XMzKyNq1oQRcSxjTRf08S0U4ApTYyrBXarYGlmZrYB8ZkVzMwsKweRmZll5SAyM7OsHERmZpaVg8jMzLJyEJmZWVYOIjMzy8pBZGZmWTmIzMwsKweRmZll5SAyM7OsHERmZpaVg8jMzLJyEJmZWVZlBZGke8tpMzMza6m1Xo9IUnfgAxQXt9sSUBq1OdCryrWZmVkH0NyF8b4MnAlsB0zj3SB6A/hp9coyM7OOYq1BFBGXA5dLOi0irmylmszMrAMp61LhEXGlpE8C/UrniYhJVarLzMw6iLKCSNINwI7AdGBVag7AQWRmZuulrCACaoBdIyKqWYyZmXU85f6OaCbw4WoWYmZmHVO5PaIewGxJjwPL6xsj4vCqVGVmZh1GuUE0rppFmJlZx1XuUXP3V7sQMzPrmMo9au7fFEfJAWwEdAXejIjNq1WYmZl1DOX2iDarH5YkYASwZ7WKMjOzjqPFZ9+Owu3AAZUvx8zMOppyN80dVXK3E8XvipZVpSIzM+tQyj1q7rCS4ZXAPIrNc2ZmZuul3H1EJ1a7EDMz65jKvTBeb0m3SXo53aZI6l3t4szMrP0r92CFa4E7KK5LtB1wZ2ozMzNbL+UGUc+IuDYiVqbbdUDP5maSNDH1oGaWtG0laaqk59LfLVO7JF0haY6kGZL2KJlnTJr+OUljWvgYzcxsA1ZuEC2RdLykzul2PLCkjPmuAw5s0PYt4N6IGADcm+4DHAQMSLexwFVQBBdwPvAJYChwfn14mZlZ21duEJ0EHAO8CCwCjgZOaG6miHgAeLVB8wjg+jR8PXBESfuk9DulR4EtJG1L8XulqRHxakT8C5jK+8PNzMzaqHIP374QGJOCoL6XcjFFQLXUNhGxKA2/CGyThnsBC0qmq0ttTbWbmVk7UG6PaFB9CAFExKvA7uu78nShvYpdbE/SWEm1kmoXL15cqcWamVkVlRtEnUr3y6QeUbm9qYZeSpvcSH9fTu0LgT4l0/VObU21v09ETIiImoio6dmz2WMpzMxsA1BuEF0CPCLpu5K+C/wVuGgd13kHUH/k2xjgtyXto9PRc3sCr6dNeHcD+0vaMoXh/qnNzMzagXLPrDBJUi0wPDUdFRGzm5tP0o3AMKCHpDqKo99+CNws6UvAPygOggC4CzgYmAO8BZyY1v1qCr+/pekuTJsGzcysHSh781oKnmbDp8E8xzYxat9Gpg3glCaWMxGY2JJ1m5lZ29Diy0CYmZlVkoPIzMyychCZmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyychCZmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyychCZmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyychCZmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZeUgMjOzrBxEZmaWVasHkaSdJU0vub0h6UxJ4yQtLGk/uGSesyXNkfSspANau2YzM6ueLq29woh4FhgMIKkzsBC4DTgRuDQiLi6dXtKuwEhgILAdcI+knSJiVWvWbWZm1ZF709y+wPMR8Y+1TDMCuCkilkfEC8AcYGirVGdmZlWXO4hGAjeW3D9V0gxJEyVtmdp6AQtKpqlLbWZm1g5kCyJJGwGHA7ekpquAHSk22y0CLlmHZY6VVCupdvHixZUq1czMqihnj+gg4ImIeAkgIl6KiFURsRr4Be9uflsI9CmZr3dqe5+ImBARNRFR07NnzyqWbmZmlZIziI6lZLOcpG1Lxh0JzEzDdwAjJXWT1B8YADzealWamVlVtfpRcwCSNgH+A/hySfNFkgYDAcyrHxcRsyTdDMwGVgKn+Ig5M7P2I0sQRcSbwNYN2katZfrxwPhq12VmZq0v91FzZmbWwTmIzMwsKweRmZll5SAyM7OsHERmZpaVg8jMzLJyEJmZWVYOIjMzy8pBZGZmWTmIzMwsKweRmZll5SAyM7OsHERmZpaVg8jMzLJyEJmZWVYOIjMzy8pBZGZmWTmIzMwsKweRmZll5SAyM7OsHERmZpaVg8jMzLJyEJmZWVYOIjMzy8pBZGZmWTmIzMwsKweRmZll5SAyM7OsHERmZpaVg8jMzLJyEJmZWVYOIjMzy8pBZGZmWWULIknzJD0labqk2tS2laSpkp5Lf7dM7ZJ0haQ5kmZI2iNX3WZmVlm5e0SfjYjBEVGT7n8LuDciBgD3pvsABwED0m0scFWrV2pmZlWRO4gaGgFcn4avB44oaZ8UhUeBLSRtm6E+MzOrsJxBFMCfJE2TNDa1bRMRi9Lwi8A2abgXsKBk3rrU9h6SxkqqlVS7ePHiatVtZmYV1CXjuveOiIWSPgRMlfRM6ciICEnRkgVGxARgAkBNTU2L5jUzszyy9YgiYmH6+zJwGzAUeKl+k1v6+3KafCHQp2T23qnNzMzauCxBJGkTSZvVDwP7AzOBO4AxabIxwG/T8B3A6HT03J7A6yWb8MzMrA3LtWluG+A2SfU1/Doi/ijpb8DNkr4E/AM4Jk1/F3AwMAd4Czix9Us2M7NqyBJEETEX+Hgj7UuAfRtpD+CUVijNzMxa2YZ2+LaZmXUwDiIzM8vKQWRmZlk5iMzMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyychCZmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyychCZmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyychCZmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZdUldwFm1rT5F34sdwnrpe95T+UuwdoA94jMzCwrB5GZmWXV6kEkqY+kP0uaLWmWpDNS+zhJCyVNT7eDS+Y5W9IcSc9KOqC1azYzs+rJsY9oJXBWRDwhaTNgmqSpadylEXFx6cSSdgVGAgOB7YB7JO0UEatatWozM6uKVu8RRcSiiHgiDf8beBrotZZZRgA3RcTyiHgBmAMMrX6lZmbWGrLuI5LUD9gdeCw1nSpphqSJkrZMbb2ABSWz1bH24DIzszYkWxBJ2hSYApwZEW8AVwE7AoOBRcAl67DMsZJqJdUuXry4kuWamVmVZAkiSV0pQmhyRNwKEBEvRcSqiFgN/IJ3N78tBPqUzN47tb1PREyIiJqIqOnZs2f1HoCZmVVMjqPmBFwDPB0RPylp37ZksiOBmWn4DmCkpG6S+gMDgMdbq14zM6uuHEfNfQoYBTwlaXpqOwc4VtJgIIB5wJcBImKWpJuB2RRH3J3iI+bMzNqPVg+iiHgIUCOj7lrLPOOB8VUryszMsvGZFczMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyychCZmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyychCZmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZdXqlwo3M7PC/As/lruEddb3vKcqtiz3iMzMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyychCZmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyychCZmVlWbSaIJB0o6VlJcyR9K3c9ZmZWGW0iiCR1Bn4GHATsChwrade8VZmZWSW0iSAChgJzImJuRLwD3ASMyFyTmZlVQFsJol7AgpL7danNzMzauHZ1qXBJY4Gx6e5SSc/mrKe1bA89gFdy17HOzlfuCjZYfm3btzb9+rb8td2+qRFtJYgWAn1K7vdObe8REROACa1V1IZCUm1E1OSuwyrPr2375te30FY2zf0NGCCpv6SNgJHAHZlrMjOzCmgTPaKIWCnpVOBuoDMwMSJmZS7LzMwqoE0EEUBE3AXclbuODVSH2xzZgfi1bd/8+gKKiNw1mJlZB9ZW9hGZmVk75SBqQySFpEtK7n9N0riMJdl6UuEhSQeVtH1e0h9z1tWWrO//haTDmzttmKR+kr64HmWWTdIJkrZrjXWl9dVIuqK11tcYB1Hbshw4SlKP3IVYZUSxbfxk4CeSukvaFPg+cEreytqU9fq/iIg7IuKHzUzWD2hREEla133wJwAVDaK11RIRtRFxeiXX11IOorZlJcXOza82HJG+sd0naYakeyX1bf3ybF1ExEzgTuCbwHnAr4BvS3pc0pOSRgBIGpjapqfXeUDGsjck6/V/kXogP03D10m6QtJfJc2VdHSa7IfAPum5/6qkzpJ+LOlvadlfTvMPk/SgpDuA2en+XyT9r6RnJE2WpDTtEEn3S5om6W5J26b11QCT07o2blDr6ZJmp3XelNo2kTSxkffLCZLukHQfcK+kmyQdUrKs6yQdnWr8XWrbVNK1kp5K6/hcat9f0iOSnpB0S/rCVDkR4VsbuQFLgc2BecAHga8B49K4O4Exafgk4Pbc9frWotd2E+BZ4CngB8DxqX0L4P/S+CuB41L7RsDGueveEG7r+39B0QP5aRq+DriF4kv6rhTnuAQYBvyuZJ6xwHfScDegFuifpnsT6F8y3+sUP8LvBDwC7A10Bf4K9EzTfYHiZykAfwFqmnis/wS61b830t/vN/F+OYHidGhbpXFHAteXvH8WABuXPjbgR8BlJevbkuLsDw8Am6S2bwLnVfI1bDOHb1shIt6QNAk4HXi7ZNRewFFp+AbgotauzdZdRLwp6TcUH6rHAIdJ+loa3R3oS/Eh9m1JvYFbI+K5PNVueCr8f3F7RKym6NFs08Q0+wODSnpMHwQGAO8Aj0fECyXTPh4RdQCSplNs5nsN2A2YmjpInYFFZdQ2g6K3dDtwe0kthzfyfgGYGhGvpuE/AJdL6gYcCDwQEW+n9dfbj+KEAQBExL8kHUoRyg+naTeieC9WjIOobboMeAK4NnMdVlmr003A5yKi4bkSn5b0GHAIcJekL0fEfa1d5AbsMirzf7G8ZLipE6oJOC0i7n5PozSMokfU1PJWUXzuCpgVEXu1sLZDgE8Dh1F8KfkYTbxfJH2itJaIWCbpL8ABFD2wm8pcpygC7dgW1lo27yNqg9I3nJuBL5U0/5V3v8kcBzzY2nVZxdwNnFayL2H39HcHYG5EXAH8FhiUr8QNT5X/L/4NbFZy/27gvyV1BZC0k6RNWrC8Z4GekvZK83eVNLCJdZGm6QT0iYg/U2we+yCwKU28X5rwG+BEYB+gsSMzp1JyoIykLYFHgU9J+khq20TSTi14rM1yELVdl1Bsu613GnCipBnAKOCMLFVZJXyXYh/CDEmz0n0oNtnNTJt3dgMm5Slvg1at/4sZwCpJf5f0VeCXwGzgCUkzgZ/Tgi1MUVxX7WjgR5L+DkwHPplGXwdc3cjBCp2BX0l6CngSuCIiXqPp90tj/gR8Brgn1dDQ94AtJc1MdX02IhZT7G+6MT2PjwAfLfexlsNnVjAzs6zcIzIzs6wcRGZmlpWDyMzMsnIQmZlZVg4iMzPLykFk1oCk3pJ+K+k5Sc9LulzFJerXNs88pZNuSvrreqx7T0mPpUN3n1aVz66ukjMvp3OOfbK5ecwqzUFkViL9KPBWitO8DAB2ovjR4PhylxER6/Nhfj0wNiIGU/xW6Ob1WNZaSeoS7z3z8jDe/S2LWatxEJm913BgWURcCxARqyjO6nySpK9IulXSH1NvqdHzlklamv626MzLafYPkc45FhGrImJ2mr6pMyx3lnRx+gHiDEmnpfbSHlpNOrULksZJukHSw8ANqcbfSepHcTmKr6be2D6SXig5c8DmpffNKsnnmjN7r4HAtNKGdELN+RT/L4OB3SnOH/aspCsjYsFalrd7WuY/gYcpTpXyGMWZtEdExGJJX6DocZ0EXJqW+xeKU7BcHxHLgG8D90XESZK2AB6XdA8wmuIkmoMjYqWkrcp4jLsCe6cTXg5Lj3GepKuBpRFxMUCq4RCKk2uOpDjR6ooylm/WIu4RmbXMvRHxegqH2cD2zUz/eETUpbM5T6cIjZ1598zL04HvUFwmgIi4kOJ6NH+iuBBb/fnA9ge+lab/C++eYXk/4OcRsTLNX3+m5bW5IyLebn4yfklxXjLSX59k16rCPSKz95pNcQ6wNSRtTvGhv5LGz6S8Ni0+83JEPA9cJekXwGJJW9P0GZabWu9K3v2i2b3BuIZnh25URDys4sJyw4DOUVzAz6zi3CMye697gQ9IGg3FPhiKE2leB7xVoXU0eeZlSYfo3XQZQBFer9H0GZanAl9WuhR0yaa5ecCQNPy5Mutq7KzPk4Bf496QVZGDyKxEFGcBPhL4vKTnKK52uQw4p4LrWNuZl0dR7COaTnEht+PSARNNnWH5l8D81P53is15ABdQXAStliLMynEncGT9wQqpbTLFVTpvXJfHalYOn33bzJqk4gqkIyJiVO5arP3yPiIza5SkK4GDgINz12Ltm3tEZmaWlfcRmZlZVg4iMzPLykFkZmZZOYjMzCwrB5GZmWXlIDIzs6z+PyOLDeXHzSXWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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77qnaur1HZGZmWTmIzMwsKweRmZll5SAyM7OsHERmZpaVg8jMzLJyEJmZdXIRwac//WnuuOOOVW033ngjBxxwQLus398jMjNbz7xw7icqurx+331ireMlcdlll3HUUUfxuc99juXLl/Otb32L3//+9xWtoykOIjMzY5ddduGLX/wiP/7xj3nrrbc47rjjGD9+PLNmzWLZsmWMGzeO4cOH8+STT3LiiSfy7rvvsnLlSiZPnszAgQPbtG4HkZmZATB27Fh23313NtpoIw455BD23XdfJk6cyGuvvcbQoUPZb7/9uOyyyzjzzDMZOXIk7777LitWrGjzeh1EZmYGQK9evTjmmGPYZJNNuOGGG7jttts4//zzAXjnnXd44YUX2GuvvRg/fjz19fUcccQRbd4bAgeRmZmVdOnShS5duhARTJ48mY997GOrjd9pp53YY489+N3vfsdBBx3Er371K/bdd9+2rbNNc5uZ2QZp//3355JLLiEiAHj88ccBmDt3LjvssANnnHEGw4cPZ+bMmW1el4PIzMze5zvf+Q7Lli1j1113ZdCgQXznO98B4IYbbmCXXXZh8ODBzJo1i+OPb/uVwtWQdhua2traqKura9a0Q74+qcrVVFeOS8abWeU89dRT7LTTTrnLqJjGtkfS9IiobWx67xGZmVlWDiIzM8vKQWRmZlk5iMzM1gMbyvn61myHg8jMLLOePXuyePHiDh9GEcHixYvp2bNni+bzF1rNzDLr27cv9fX1LFq0KHcpbdazZ0/69u3bonkcRGZmmXXv3p0BAwbkLiMbH5ozM7OsHERmZpaVg8jMzLJyEJmZWVYOIjMzy6pqQSRpoqSXJc0qtV0vaUa6zZM0I7X3l/TP0rjLSvMMkfSEpDmSLpakatVsZmbtr5rdt68EfgGsurR1RBzTMCzpAuD10vTPRcTgRpZzKfBl4FHgduAA4I7Kl2tmZjlUbY8oIu4HXm1sXNqrORq4dm3LkLQNsFlEPBLFV44nAYdVuFQzM8so1zmifYCFEfFsqW2ApMcl3Sdpn9TWB6gvTVOf2holaYykOkl1G8I3lM3MOoNcQXQsq+8NLQD6RcRuwH8A/ytps5YuNCImRERtRNTW1NRUqFQzM6umdr/Ej6RuwBHAkIa2iFgKLE3D0yU9B3wUmA+UL1rUN7WZmdkGIse15vYDno6IVYfcJNUAr0bECkk7AAOBuRHxqqQ3JO1J0VnheOCSDDVbB9aRfwrePwNvnUE1u29fCzwMfExSvaST06gRvL+TwmeAmak79/8Bp0REQ0eHfwf+B5gDPId7zJmZbVCqtkcUEcc20X5CI22TgclNTF8H7FLR4szMbL3hKyuYmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyychCZmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyychCZmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyychCZmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyyqloQSZoo6WVJs0pt4yTNlzQj3Q4qjTtH0hxJz0jav9R+QGqbI+mb1arXzMzyqOYe0ZXAAY20XxgRg9PtdgBJOwMjgEFpnv+W1FVSV+CXwIHAzsCxaVozM9tAdKvWgiPifkn9mzn5cOC6iFgK/E3SHGBoGjcnIuYCSLouTTu70vWamVkeOc4RnSZpZjp0t3lq6wO8WJqmPrU11W5mZhuI9g6iS4EdgcHAAuCCSi5c0hhJdZLqFi1aVMlFm5lZlbRrEEXEwohYERErgV/z3uG3+cB2pUn7pram2pta/oSIqI2I2pqamsoWb2ZmVdGuQSRpm9Ldw4GGHnVTgBGSekgaAAwEpgF/BgZKGiBpI4oODVPas2YzM6uuqnVWkHQtMAzoLakeGAsMkzQYCGAe8BWAiHhS0g0UnRCWA6dGxIq0nNOAO4GuwMSIeLJaNZuZWfurZq+5Yxtpvnwt048HxjfSfjtwewVLMzOz9YivrGBmZlk5iMzMLCsHkZmZZeUgMjOzrKrWWcHazwvnfiJ3CW3S77tP5C7BzDLyHpGZmWXlIDIzs6wcRGZmlpWDyMzMsnIQmZlZVg4iMzPLyt23zazDGvL1SblLaJPpPz0+dwnrBe8RmZlZVg4iMzPLykFkZmZZOYjMzCwrB5GZmWXlIDIzs6wcRGZmlpWDyMzMsnIQmZlZVg4iMzPLykFkZmZZOYjMzCwrB5GZmWXlIDIzs6wcRGZmlpWDyMzMsnIQmZlZVg4iMzPLykFkZmZZOYjMzCwrB5GZmWVVtSCSNFHSy5Jmldp+KulpSTMl3SzpQ6m9v6R/SpqRbpeV5hki6QlJcyRdLEnVqtnMzNpfNfeIrgQOWKNtKrBLROwK/BU4pzTuuYgYnG6nlNovBb4MDEy3NZdpZmYdWNWCKCLuB15do+0PEbE83X0E6Lu2ZUjaBtgsIh6JiAAmAYdVoVwzM8sk5zmik4A7SvcHSHpc0n2S9kltfYD60jT1qc3MzDYQ3XKsVNJ/AcuBa1LTAqBfRCyWNAS4RdKgVix3DDAGoF+/fpUq18zMqqjd94gknQAcAoxMh9uIiKURsTgNTweeAz4KzGf1w3d9U1ujImJCRNRGRG1NTU2VtsDMzCqpXYNI0gHAfwKHRsTbpfYaSV3T8A4UnRLmRsQC4A1Je6becscDt7ZnzWZmVl1VOzQn6VpgGNBbUj0wlqKXXA9gauqF/UjqIfcZ4FxJy4CVwCkR0dDR4d8peuBtTHFOqXxeyczMOriqBVFEHNtI8+VNTDsZmNzEuDpglwqWZmZm6xFfWcHMzLJyEJmZWVYOIjMzy8pBZGZmWTmIzMwsKweRmZll5SAyM7OsHERmZpaVg8jMzLJyEJmZWVYOIjMzy8pBZGZmWTmIzMwsKweRmZll5SAyM7OsmhVEku5uTpuZmVlLrfWH8ST1BD5A8SurmwNKozYD+lS5NjMz6wTW9QutXwHOArYFpvNeEL0B/KJ6ZZmZWWex1iCKiJ8DP5d0ekRc0k41mZlZJ7KuPSIAIuISSZ8C+pfniYhJVarLzMw6iWYFkaSrgR2BGcCK1ByAg8jMzNqkWUEE1AI7R0RUsxgzM+t8mvs9olnAh6tZiJmZdU7N3SPqDcyWNA1Y2tAYEYdWpSozM+s0mhtE46pZhJmZdV7N7TV3X7ULMTOzzqm5vebepOglB7AR0B14KyI2q1ZhZmbWOTR3j2jThmFJAoYDe1arKDMz6zxafPXtKNwC7F/5cszMrLNp7qG5I0p3u1B8r+idqlRkZmadSnN7zX2xNLwcmEdxeM7MzKxNmnuO6MRqF2JmZp1Tc38Yr6+kmyW9nG6TJfWtdnFmZrbha25nhSuAKRS/S7QtcFtqWytJE1NwzSq1bSFpqqRn09/NU7skXSxpjqSZknYvzTM6Tf+spNEt2UAzM1u/NTeIaiLiiohYnm5XAjXNmO9K4IA12r4J3B0RA4G7032AA4GB6TYGuBSK4ALGAnsAQ4GxDeFlZmYdX3ODaLGk4yR1TbfjgMXrmiki7gdeXaN5OHBVGr4KOKzUPil1D38E+JCkbSi6iU+NiFcj4h/AVN4fbmZm1kE1N4hOAo4GXgIWAEcCJ7RynVtHxII0/BKwdRruA7xYmq4+tTXVbmZmG4DmBtG5wOiIqImIrSiC6XttXXn6faOK/caRpDGS6iTVLVq0qFKLNTOzKmpuEO2aDosBEBGvAru1cp0L0yE30t+XU/t8YLvSdH1TW1Pt7xMREyKiNiJqa2qacwrLzMxya24QdSl3EEgdCJr7Zdg1TQEaer6NBm4ttR+fes/tCbyeDuHdCXxB0uaphi+kNjMz2wA0N0wuAB6WdGO6fxQwfl0zSboWGAb0llRP0fvtR8ANkk4Gnqc49wRwO3AQMAd4GzgRir0vSd8H/pymOzftkZmZ2QaguVdWmCSpDtg3NR0REbObMd+xTYz6fCPTBnBqE8uZCExsTq1mZtaxNPvwWgqedYaPmZlZS7T4ZyDMzMwqyUFkZmZZOYjMzCwrB5GZmWXlIDIzs6wcRGZmlpWDyMzMsnIQmZlZVg4iMzPLykFkZmZZOYjMzCwrB5GZmWXlIDIzs6wcRGZmlpWDyMzMsnIQmZlZVg4iMzPLykFkZmZZOYjMzCwrB5GZmWXlIDIzs6wcRGZmlpWDyMzMsnIQmZlZVg4iMzPLykFkZmZZOYjMzCwrB5GZmWXlIDIzs6wcRGZmlpWDyMzMsnIQmZlZVu0eRJI+JmlG6faGpLMkjZM0v9R+UGmecyTNkfSMpP3bu2YzM6uebu29woh4BhgMIKkrMB+4GTgRuDAizi9PL2lnYAQwCNgWuEvSRyNiRXvWbWZm1ZH70Nzngeci4vm1TDMcuC4ilkbE34A5wNB2qc7MzKoudxCNAK4t3T9N0kxJEyVtntr6AC+WpqlPbWZmtgHIFkSSNgIOBW5MTZcCO1IctlsAXNCKZY6RVCepbtGiRZUq1czMqijnHtGBwGMRsRAgIhZGxIqIWAn8mvcOv80HtivN1ze1vU9ETIiI2oiorampqWLpZmZWKTmD6FhKh+UkbVMadzgwKw1PAUZI6iFpADAQmNZuVZqZWVW1e685AEm9gH8BvlJq/omkwUAA8xrGRcSTkm4AZgPLgVPdY87MbMORJYgi4i1gyzXaRq1l+vHA+GrXZWZm7S93rzkzM+vkHERmZpaVg8jMzLJyEJmZWVYOIjMzy8pBZGZmWTmIzMwsKweRmZll5SAyM7OsHERmZpaVg8jMzLJyEJmZWVYOIjMzy8pBZGZmWTmIzMwsKweRmZll5SAyM7OsHERmZpaVg8jMzLJyEJmZWVYOIjMzy8pBZGZmWTmIzMwsKweRmZll5SAyM7OsHERmZpaVg8jMzLJyEJmZWVYOIjMzy8pBZGZmWTmIzMwsKweRmZll5SAyM7OssgWRpHmSnpA0Q1JdattC0lRJz6a/m6d2SbpY0hxJMyXtnqtuMzOrrNx7RJ+LiMERUZvufxO4OyIGAnen+wAHAgPTbQxwabtXamZmVZE7iNY0HLgqDV8FHFZqnxSFR4APSdomQ31mZlZhOYMogD9Imi5pTGrbOiIWpOGXgK3TcB/gxdK89anNzMw6uG4Z1/3piJgvaStgqqSnyyMjIiRFSxaYAm0MQL9+/SpXqZmZVU22PaKImJ/+vgzcDAwFFjYcckt/X06Tzwe2K83eN7WtucwJEVEbEbU1NTXVLN/MzCokSxBJ6iVp04Zh4AvALGAKMDpNNhq4NQ1PAY5Pvef2BF4vHcIzM7MOLNehua2BmyU11PC/EfF7SX8GbpB0MvA8cHSa/nbgIGAO8DZwYvuXbGZm1ZAliCJiLvDJRtoXA59vpD2AU9uhNDMza2frW/dtMzPrZBxEZmaWlYPIzMyychCZmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyychCZmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyychCZmVlWDiIzM8vKQWRmZlk5iMzMLCsHkZmZZeUgMjOzrBxEZmaWlYPIzMyy6pa7ADNr2gvnfiJ3CW3S77tP5C7BOgDvEZmZWVYOIjMzy8pBZGZmWTmIzMwsKweRmZll1e5BJGk7SX+UNFvSk5LOTO3jJM2XNCPdDirNc46kOZKekbR/e9dsZmbVk6P79nLg7Ih4TNKmwHRJU9O4CyPi/PLEknYGRgCDgG2BuyR9NCJWtGvVZmZWFe2+RxQRCyLisTT8JvAU0GctswwHrouIpRHxN2AOMLT6lZqZWXvIeo5IUn9gN+DR1HSapJmSJkraPLX1AV4szVbP2oPLzMw6kGxBJGkTYDJwVkS8AVwK7AgMBhYAF7RimWMk1UmqW7RoUSXLNTOzKskSRJK6U4TQNRFxE0BELIyIFRGxEvg17x1+mw9sV5q9b2p7n4iYEBG1EVFbU1NTvQ0wM7OKydFrTsDlwFMR8bNS+zalyQ4HZqXhKcAIST0kDQAGAtPaq14zM6uuHL3m9gZGAU9ImpHavgUcK2kwEMA84CsAEfGkpBuA2RQ97k51jzkzsw1HuwdRRDwIqJFRt69lnvHA+KoVZWZm2fjKCmZmlpWDyMzMsnIQmZlZVg4iMzPLykFkZmZZOYjMzCwrB5GZmWXlIDIzs6wcRGZmlpWDyMzMsnIQmZlZVg4iMzPLykFkZmZZOYjMzCwrB5GZmWXlIDIzs6wcRGZmlpWDyMzMsmr3nwo3M7PCC+d+IncJrdbvu09UbFneIzIzs6wcRGZmlpWDyMzMsnIQmZlZVg4iMzPLykFkZmZZOYjMzCwrB5GZmWXlIDIzs6wcRGZmlpWDyMzMsnIQmZlZVg4iMzPLykFkZmZZdZggknSApGckzZH0zdz1mJlZZXSIIJLUFfglcCCwM3CspJ3zVmVmZpXQIYIIGArMiYi5EfEucB0wPHNNZmZWAR0liPoAL5bu16c2MzPr4DaonwqXNAYYk+4ukfRMznray/bQG3gldx2tNla5K1hv+bndsHXo57flz+32TY3oKEE0H9iudL9valtNREwAJrRXUesLSXURUZu7Dqs8P7cbNj+/hY5yaO7PwEBJAyRtBIwApmSuyczMKqBD7BFFxHJJpwF3Al2BiRHxZOayzMysAjpEEAFExO3A7bnrWE91usORnYif2w2bn19AEZG7BjMz68Q6yjkiMzPbQDmIOhBJIemC0v2vSRqXsSRrIxUelHRgqe0oSb/PWVdH0tb/C0mHruuyYZL6S/pSG8psNkknSNq2PdaV1lcr6eL2Wl9jHEQdy1LgCEm9cxdilRHFsfFTgJ9J6ilpE+CHwKl5K+tQ2vR/ERFTIuJH65isP9CiIJLU2nPwJwAVDaK11RIRdRFxRiXX11IOoo5lOcXJza+uOSJ9YrtH0kxJd0vq1/7lWWtExCzgNuAbwHeB3wD/JWmapMclDQeQNCi1zUjP88CMZa9P2vR/kfZAfpGGr5R0saQ/SZor6cg02Y+AfdJj/1VJXSX9VNKf07K/kuYfJukBSVOA2en+vZL+T9LTkq6RpDTtEEn3SZou6U5J26T11QLXpHVtvEatZ0iandZ5XWrrJWliI6+XEyRNkXQPcLek6yQdXFrWlZKOTDX+NrVtIukKSU+kdfxrav+CpIclPSbpxvSBqXIiwrcOcgOWAJsB84APAl8DxqVxtwGj0/BJwC256/WtRc9tL+AZ4AngPOC41P4h4K9p/CXAyNS+EbBx7rrXh1tb/y8o9kB+kYavBG6k+JC+M8U1LgGGAb8tzTMG+HYa7gHUAQPSdG8BA0rzvU7xJfwuwMPAp4HuwJ+AmjTdMRRfSwG4F6htYlv/DvRoeG2kvz9s4vVyAsXl0LZI4w4Hriq9fl4ENi5vG/Bj4KLS+januPrD/UCv1PYN4LuVfA47TPdtK0TEG5ImAWcA/yyN2gs4Ig1fDfykvWuz1ouItyRdT/GmejTwRUlfS6N7Av0o3sT+S1Jf4KaIeDZPteufCv9f3BIRKyn2aLZuYpovALuW9pg+CAwE3gWmRcTfStNOi4h6AEkzKA7zvQbsAkxNO0hdgQXNqG0mxd7SLcAtpVoObeT1AjA1Il5Nw3cAP5fUAzgAuD8i/pnW32A/igsGABAR/5B0CEUoP5Sm3YjitVgxDqKO6SLgMeCKzHVYZa1MNwH/GhFrXivxKUmPAgcDt0v6SkTc095FrscuojL/F0tLw01dUE3A6RFx52qN0jCKPaKmlreC4n1XwJMRsVcLazsY+AzwRYoPJZ+gideLpD3KtUTEO5LuBfan2AO7rpnrFEWgHdvCWpvN54g6oPQJ5wbg5FLzn3jvk8xI4IH2rssq5k7g9NK5hN3S3x2AuRFxMXArsGu+Etc/Vf6/eBPYtHT/TuD/SeoOIOmjknq1YHnPADWS9krzd5c0qIl1kabpAmwXEX+kODz2QWATmni9NOF64ERgH6CxnplTKXWUkbQ58Aiwt6SPpLZekj7agm1dJwdRx3UBxbHbBqcDJ0qaCYwCzsxSlVXC9ynOIcyU9GS6D8Uhu1np8M4uwKQ85a3XqvV/MRNYIekvkr4K/A8wG3hM0izgV7TgCFMUv6t2JPBjSX8BZgCfSqOvBC5rpLNCV+A3kp4AHgcujojXaPr10pg/AJ8F7ko1rOkHwOaSZqW6PhcRiyjON12bHseHgY83d1ubw1dWMDOzrLxHZGZmWTmIzMwsKweRmZll5SAyM7OsHERmZpaVg8isGSRtmbrTzpD0kqT5pfsbNWP+VdfzamTcIekaYX9J1xH7SuW3oHkkHSZp51zrt87JV1Ywa4aIWAwMBlDxEwNLIuL8ti43fSFyAjA0IurT5Vf6t3W5raylG3AY8FuK78iYtQvvEZm1UmNXT07tH5F0V9rDeUzSjmmWTfT+qzBvSvGBcDFARCxtuFRLw9WRS+tbkv4Ok3S/pN9JekbSZelb90haIulCSU+quNp0TWofLOmRdEXlm9M35lFxZeiLJNVRfFv/UOCnaU+voW6zqnIQmbWOKK6GfWREDAEmAuPTuGuAX0bEJym+Ld9wMcvdgLMoLiC5A7B3uizNFOB5SddKGtkQKuswlOKqATsDO/LehT17AXURMQi4Dxib2icB34iIXSmu8D22tKyNIqI2IsanWr4eEYMj4rnmPxxmrecgMmudHrx39eQZwLeBvpI2BfpExM1QXGgyIt5O80yLiPp0ZecZpENwEfFvwOeBaRQ/YTCxGeufFhFzI2IFcC3FTwtAcdHU69Pwb4BPS/ogxU8G3Jfar6K4cGaD6zHLyOeIzFqn0asnpyBqSmNXYQYgIp4AnpB0NfA3imt7LSd9WEx7SeVOEWtem6upa3U15xpea14t2qxdeY/IrHWW0sjVkyPiTaBe0mGpvYekDzS1EBW/iDms1DQYeD4NzwOGpOFDKS5s2WCopAEpoI4BHkztXSgupgnFT1s/GBGvA/+QtE9qH0Vx2K4xjV752ayaHERmrbOSpq+ePAo4I12p+E/Ah9eyHAH/mTodzAC+R7E3BPBr4LNp+Xux+p7Ln4FfAE9R7EHdnNrfogipWcC+wLmpfTRFJ4SZFGF3Lo27Dvh66k7uzgrWLnz1bbMOJu1BfS0iDmlk3JKI2KTdizJrA+8RmZlZVt4jMjOzrLxHZGZmWTmIzMwsKweRmZll5SAyM7OsHERmZpaVg8jMzLL6/32bEiMwq2FOAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Bk4FjI2LNNrZbktSP2hZEmflwR48mM/8K3AWsB+wMdPRozgR2KdM7A2dl47fAGhGxLvB+4MrMfCIznwSuBPrn576SpLbrl3NEETEWeAfwO2CdzHy4LHqE5tAdNCH1YMtqc0tZV+WL7+PAiJgZETPnzZvXt09AktQ2bQ+iiFgVuBA4PDP/0rosmxNUfXKSKjOnZ+akzJw0evTovtikJPWbdp2v729L8zzaGkQRMZwmhM7JzItK8aPlkBvl38dK+UPA+i2rjyllXZVL0gph5MiRzJ8/f8CHUWYyf/58Ro4c2av12vaD1nIV3GnAXZn5by2LLgX2A75a/r2kpfzgiDiP5sKEpzPz4Yi4AvhKywUK7wOOale7Jam/jRkzhrlz57IinFYYOXIkY8aM6dU67RxZYUtgH+D2iLi1lH2eJoDOj4hPAPcDu5dll9Ncun0PzeXbBwBk5hMR8SXg5lLvuMx8oo3tlqR+NXz4cDbaaKPazaimbUGUmTcA0cXibTupn8BBXWxrBjCj71onSVpeOLKCJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKqG1W6Alt0Dx729dhOWyQbH3F67CZIqskckSarKIJIkVeWhOUkD1hafPat2E5bJrG/sW7sJywV7RJKkqgwiSVJVBpEkqSqDSJJUlUEkSarKIJIkVWUQSZKqMogkSVUZRJKkqgwiSVJVBpEkqSqDSJJUlUEkSarKIJIkVWUQSZKqMogkSVW1LYgiYkZEPBYRc1rKpkXEQxFxa3ns2LLsqIi4JyL+GBHvbynfvpTdExFHtqu9kqQ62tkjOgPYvpPyb2bmxPK4HCAiNgH2BCaUdb4XEUMjYijwXWAHYBNgr1JXkrSCaNutwjPz+ogY28PqOwPnZebzwH9HxD3A5LLsnsy8FyAizit17+zr9kqS6qhxjujgiJhdDt2tWcrWAx5sqTO3lHVVLklaQfR3EH0fGAdMBB4GTuqrDUfEgRExMyJmzps3r682K0lqs34Nosx8NDNfysyXgR/yyuG3h4D1W6qOKWVdlXe27emZOSkzJ40ePbrvGy9Jaot+DaKIWLdldleg44q6S4E9I2JERGwEjAduAm4GxkfERhGxEs0FDZf2Z5slSe3VtosVIuJcYAowKiLmAscCUyJiIpDAfcA/AWTmHRFxPs1FCC8CB2XmS2U7BwNXAEOBGZl5R7vaLEnqf+28am6vTopPW0L944HjOym/HLi8D5smSVqOOLKCJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKmqYbUbILXbFp89q3YTltqsb+xbuwlS29kjkiRVZRBJkqoyiCRJVRlEkqSqDCJJUlUGkSSpKoNIklSVQSRJqsogkiRV1aMgioire1ImSVJvLXGIn4gYCbwOGBURawJRFq0OrNfmtkmSBoHuxpr7J+Bw4E3ALF4Jor8A32lfsyRJg8USgygzTwZOjohDMvOUfmqTJGkQ6dHo25l5SkS8Fxjbuk5mDtxhjSVJy4UeBVFEnA2MA24FXirFCRhEkqRl0tP7EU0CNsnMbGdjJEmDT09/RzQHeGM7GyJJGpx62iMaBdwZETcBz3cUZuaH2tIqSdKg0dMgmtbORkiSBq+eXjX3y3Y3RJI0OPX0qrm/0lwlB7ASMBx4NjNXb1fDJEmDQ097RKt1TEdEADsD725XoyRJg0evR9/Oxk+A9/d9cyRJg01PD819uGV2CM3viha0pUWSpEGlp1fNfbBl+kXgPprDc5IkLZOeniM6oN0NkSQNTj29Md6YiLg4Ih4rjwsjYky7GydJWvH19GKF04FLae5L9Cbgp6VMkqRl0tMgGp2Zp2fmi+VxBjC6je2SJA0SPQ2i+RHxsYgYWh4fA+a3s2GSpMGhp0H0cWB34BHgYWA3YP82tUmSNIj09PLt44D9MvNJgIhYCziRJqAkSVpqPe0RbdYRQgCZ+QTwjvY0SZI0mPQ0iIZExJodM6VH1NPelCRJXeppmJwE3BgRF5T5jwDHt6dJkqTBpKcjK5wVETOBqaXow5l5Z/uaJUkaLHp8eK0Ej+EjSepTvb4NhCRJfckgkiRVZRBJkqoyiCRJVRlEkqSq2hZEETGj3LtoTkvZWhFxZUTcXf5ds5RHRHw7Iu6JiNkR8c6WdfYr9e+OiP3a1V5JUh3t7BGdAWy/WNmRwNWZOR64uswD7ACML48Dge/DohEcjgXeBUwGjm0d4UGSNPC1LYgy83rgicWKdwbOLNNnAru0lJ+Vjd8Ca0TEusD7gSsz84ky1t2VvDbcJEkDWH+fI1onMx8u048A65Tp9YAHW+rNLWVdlUuSVhDVLlbIzASyr7YXEQdGxMyImDlv3ry+2qwkqc36O4geLYfcKP8+VsofAtZvqTemlHVV/hqZOT0zJ2XmpNGjvYu5JA0U/R1ElwIdV77tB1zSUr5vuXru3cDT5RDeFcD7ImLNcpHC+0qZJGkF0bZ7CkXEucAUYFREzKW5+u2rwPkR8QngfprbjwNcDuwI3AM8BxwAzQ34IuJLwM2l3nHlpnySpBVE24IoM/fqYtG2ndRN4KAutjMDmNGHTZMkLUccWUGSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqqoSRBFxX0TcHhG3RsTMUrZWRFwZEXeXf9cs5RER346IeyJidkS8s0abJUntUbNHtE1mTszMSWX+SODqzBwPXF3mAXYAxpfHgcD3+72lkqS2WZ4Oze0MnFmmzwR2aSk/Kxu/BdaIiHUrtE+S1Aa1giiBX0TErIg4sJStk5kPl+lHgHXK9HrAgy3rzi1lrxIRB0bEzIiYOW/evHa1W5LUx4ZV2u9WmflQRLwBuDIi/tC6MDMzIrI3G8zM6cB0gEmTJvVqXUlSPVV6RJn5UPn3MeBiYDLwaMcht/LvY6X6Q8D6LauPKWWSpBVAvwdRRKwSEat1TAPvA+YAlwL7lWr7AZeU6UuBfcvVc+8Gnm45hCdJGuBqHJpbB7g4Ijr2/+PM/HlE3AycHxGfAO4Hdi/1Lwd2BO4BngMO6P8mS5Lapd+DKDPvBTbvpHw+sG0n5Qkc1A9NkyRVsDxdvi1JGoQMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqaljtBkjq2gPHvb12E5bJBsfcXrsJGgDsEUmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqjKIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqvIOrZJUyUC+A29f3n3XHpEkqSqDSJJUlUEkSapqwARRRGwfEX+MiHsi4sja7ZEk9Y0BEUQRMRT4LrADsAmwV0RsUrdVkqS+MCCCCJgM3JOZ92bmC8B5wM6V2yRJ6gMDJYjWAx5smZ9byiRJA9wK8zuiiDgQOLDMPhMRf6zZnv60IYwCHq/djqV2bNRuwXLL93bFNqDf396/txt2tWCgBNFDwPot82NK2SKZOR2Y3p+NWl5ExMzMnFS7Hep7vrcrNt/fxkA5NHczMD4iNoqIlYA9gUsrt0mS1AcGRI8oM1+MiIOBK4ChwIzMvKNysyRJfWBABBFAZl4OXF67HcupQXlIcpDwvV2x+f4CkZm12yBJGsQGyjkiSdIKyiDqoYjIiPhRy/ywiJgXEf+1lNtbIyL+pWV+Sk+2FRFjI+KjS7PPdoiIXVpHuYiI6yJiUF4FFBFjIuKSiLg7Iv4cESeXi2s0wEXE2hFxa3k8EhEPtcz7Hi8jg6jnngU2jYiVy/zfs9gl5L20BvAv3VXqxFhguQkiYBeaYZcGtYgI4CLgJ5k5HvgbYFXg+KoNW4KIGDDniGvLzPmZOTEzJwKnAt/smC+jvSw3BuL7ahD1zuXAB8r0XsC5HQsiYq2I+ElEzI6I30bEZqV8WkTMKD2FeyPi0LLKV4Fx5RvVN0rZqhHxnxHxh4g4p/xxW9xXga3Lep+KiJERcXpE3B4Rt0TENp01PCLOiIjvl7bdW3pgMyLirog4o6XeXmVbcyLiay3lz0TE8RFxW9nGOhHxXuBDwDdKe8aV6h+JiJsi4k8RsXVvX+QBaiqwIDNPB8jMl4BPAR+PiNdFxP4RcVFE/Lz0mL7esWJEvC8iboyI30fEBRGxauuGI2JcRPy+ZX58x3xEbBERv4yIWRFxRUSsW8r/MSJuLu/XhRHxulJ+RkScGhG/A76OltaQiJgFEBGblyMmG5T5P5f3fGxEXFP+JlzdsbxDRAwpn4XRLfP3RMTo8riwvIc3R8SWpc7k8lm5JSJ+ExFvLeX7R8SlEXENcHW/vhJ9ITN99OABPANsBvwnMBK4FZgC/FdZfgpwbJmeCtxapqcBvwFG0PyKej4wnKZnM6dl+1OAp2l+rDsEuBHYqpN2LNpnmT+C5nJ2gLcBDwAjO1nvDJox+oJmnL6/AG8v+5oFTATeVNYfTXNF5TXALmX9BD5Ypr8OfKFlu7u17Oc64KQyvSNwVe33rp8+H4fSfEtevPyW8rnZH7gXeH35/NxP8yPtUcD1wCql/r8Cx3SynWuBiWX6K8Ah5XP0G2B0Kd+j5bOwdsu6XwYOaXm//gsYWvs1G6iP8n/6M8AdwOrAwTS/ddybZvSAG0u9nwL7lemP0/SWF9/WscDhZfp9wIVl+scd//+BDYC7yvTqwLAyvV1L/f1phj5bq/brszSPAdeFqykzZ0fEWJre0OKXkm8F/N9S75pyTHn1suyyzHweeD4iHgPW6WIXN2XmXICIuJUmrG7opllb0YQgmfmHiLif5rDQ7E7q/jQzMyJuBx7NzNvLvu4o+9oQuC4z55Xyc4C/BX4CvEDzBwya4Pr7JbTpopZ6Y7tp/2BydWY+DRARd9K83mvQHNr8dekAr0TzJWRx/w4cEBGfpgmcycBbgU2BK8u6Q4GHS/1NI+LLZfur0vwGr8MF2fTYtGx+A2xJ83/kK8D2NF/0flWWvwf4cJk+m857oDOAS4Bv0YTV6aV8O2CTloMiq5ee8uuBMyNiPM2Xw+Et27oyM59Y5mdVgUHUe5cCJ9L0TNbu4TrPt0y/RNev+2vqRcS7gB+UsmNoejLdiojjKYcRszmu3br9lxfb18ulTQuXsMmFWb56seTn0Lqf7uqtSO4EdmstKF9ENgDuAd5J55+DoPkDslc327+Q5tvzNcCszJwfEW8C7sjM93RS/wya3uxtEbE/zee1w7M9fE5asuuBrWm+UFxC05tN4LKebiAzH4yIRyNiKs2Xi73LoiHAuzNzQWv9iPgOcG1m7lq+FF/XsnjAvq+eI+q9GcAXO3oTLX5F+RBFxBTg8cxcUmj8FVitu51l5u/ylZOil3ayXut+/4bmD98fM/P/5SsnV3vqJuDvImJUNPeA2gv4ZTfr9Oh5DAJXA6+LiH1h0T20TgLOyMznlrDeb4EtI+ItZb1Vyvv4KuUP0hXA93nlW/MfgdER8Z6y7vCImFCWrQY8HBHDeeWPm/rWr4CPAXdn5svAEzSHozuOYvyGZjgyaN6DX71mC41/B37Eq3uqv6A5/ApAREwsk6/nlYuk9l/mZ7CcMIh6KTPnZua3O1k0DdgiImbTXFCwXzfbmU9zOGZOvHKxQk/MBl4qJ6E/BXyP5sTp7cB/APuXw4C9lpkPA0fSnI+4jeab9yXdrHYe8Nly8nRcN3VXWKW3uCvNhRp3A38CFgCf72a9eTR/UM4tn50bac71deYcmt7rL8q6L9D0wr4WEbfRnLd8b6l7NPA74NfAH5b2ealrmXkfTY/2+lJ0A/BUZj5Z5g+hOZw6G9gHOKyLTV1Kc/j09JayQ4FJ5UKHO4FPlvKvAydExC2sQEcbHFlBGiAi4jPA6zPz6NptUd+J5nd338zMwXKF6WusMIkqrcgi4mJgHM0VmVpBRMSRwD8zyA+f2iOSJFXlOSJJUlUGkSSpKoNIklSVQST1oYh4Y0ScV8YbmxURl3f2u6AebOfwjvHh+qBNy9WI7dLiDCKpj0QzHsvFNMMkjcvMLYCj6HpIpyU5HOg0iMqPZXtjLMvXiO3SqxhEUt/ZhmYopFM7CjLzNuCGiPhG+fHy7RGxByy6B9V1sdiI69GM0P4m4NqIuLbUfSYiTio/XH1PRBxTRmWeExHTSwgSEW+JiKvKD55/X35k/KoR2/v5NZG65e+IpL6zKc1Ar4v7MM3o5pvTjLZ9c0R0/Br/HcAE4H9oRkHYMjO/XQY33SYzHy/1VgF+l5lHQDNoamYeV6bPBnaiGe35HOCrmXlxRIyk+bJ5JPCZzNypr5+w1BfsEUnttxVwbma+lJmP0ozf93/KspvKsFEv0wzRM7aLbbxEM/Bph20i4ndlaKepwISIWA1YLzMvhmZ8um7GuZOWCwaR1HfuALbo5To9HZl9QceAmKWn8z2a+0C9HfghzT2OpAHJIJL6zjXAiIg4sKMgmjv1PgXsERFDo7kb59/SjHS+JEsa1bwjdB4v96jZDSAz/wrMjYhdyr5HlCvvHCFdyzWDSOojLSNwb1cu374DOIHmbpuzaUY0vwb4XGY+0s3mpgM/77hYYbH9PEXTC5pDc2uIm1sW7wMcWkZ8/g3wRl47Yru0XHGsOUlSVfaIJElVGUSSpKoMIklSVQaRJKkqg0iSVJVBJEmqyiCSJFVlEEmSqvr/+bYNAQYUxZIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Check how the frequency varies with the target\n",
    "for i in data[cols]:\n",
    "  if i != ('Churn'):\n",
    "    plt.figure(figsize=(6,6))\n",
    "    sns.countplot(x=data[i], hue=data['Churn'])\n",
    "    plt.title(f'Count of {i} wrt to Target')\n",
    "    plt.tight_layout(pad=1.4)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "fWl3d2abdqVx",
    "tags": []
   },
   "source": [
    "Observations:\n",
    "\n",
    "* Majority of folks with phones that don't have access to internet services tend to have longer retention span\n",
    "* Customers with a one year contract or two year contract tend to stay on the telco longer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 384
    },
    "id": "4CQzblcyquoQ",
    "outputId": "ef814c27-c064-430b-ea18-baeb440166bd",
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Customer churn by monthly charges\n",
    "mc_churn_yes= data[data.Churn=='Yes'].MonthlyCharges\n",
    "mc_churn_no= data[data.Churn=='No'].MonthlyCharges\n",
    "\n",
    "plt.xlabel(\"monthly charges\")\n",
    "plt.ylabel(\"Number of customer\")\n",
    "plt.title(\"Customer Churn by Monthly Charges\")\n",
    "plt.hist([mc_churn_yes,mc_churn_no], label=['Churn=Yes','Churn=No'])\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ly4uqhsOef-N",
    "tags": []
   },
   "source": [
    "The distribution is skewed to the left.\n",
    "\n",
    "Customers with less monthly charges tend to stay on the telco longer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 384
    },
    "id": "t7rMjw9QxHlt",
    "outputId": "0c3d37a2-8712-49c3-8102-ad56781521c1",
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Customer Churn by tenure\n",
    "tenure_churn_yes= data[data.Churn=='Yes'].tenure\n",
    "tenure_churn_no= data[data.Churn=='No'].tenure\n",
    "\n",
    "plt.xlabel(\"Number of months\")\n",
    "plt.ylabel(\"Number of customer\")\n",
    "plt.title(\"Customer Churn by tenure\")\n",
    "plt.hist([tenure_churn_yes, tenure_churn_no], label=['Churn=Yes','Churn=No'])\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5r6smS0CfA03",
    "tags": []
   },
   "source": [
    "The longer the tenure period the more likely the customer will stay "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 300
    },
    "id": "JkWtA_iW7qUV",
    "outputId": "5a4a2339-002f-49d2-a299-2462c126986c",
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>tenure</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>7032.000000</td>\n",
       "      <td>7032.000000</td>\n",
       "      <td>7032.000000</td>\n",
       "      <td>7032.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.162400</td>\n",
       "      <td>32.421786</td>\n",
       "      <td>64.798208</td>\n",
       "      <td>2283.300441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.368844</td>\n",
       "      <td>24.545260</td>\n",
       "      <td>30.085974</td>\n",
       "      <td>2266.771362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>18.250000</td>\n",
       "      <td>18.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>35.587500</td>\n",
       "      <td>401.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>70.350000</td>\n",
       "      <td>1397.475000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>89.862500</td>\n",
       "      <td>3794.737500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>118.750000</td>\n",
       "      <td>8684.800000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       SeniorCitizen       tenure  MonthlyCharges  TotalCharges\n",
       "count    7032.000000  7032.000000     7032.000000   7032.000000\n",
       "mean        0.162400    32.421786       64.798208   2283.300441\n",
       "std         0.368844    24.545260       30.085974   2266.771362\n",
       "min         0.000000     1.000000       18.250000     18.800000\n",
       "25%         0.000000     9.000000       35.587500    401.450000\n",
       "50%         0.000000    29.000000       70.350000   1397.475000\n",
       "75%         0.000000    55.000000       89.862500   3794.737500\n",
       "max         1.000000    72.000000      118.750000   8684.800000"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# convert Churn targe from string to integers\n",
    "# replace no with 1 and yes with 0\n",
    "data['Churn'] = data['Churn'].replace({'No':1, 'Yes':0})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "G_rB_8FLfP4x",
    "tags": []
   },
   "source": [
    "# Feature Engineering\n",
    "\n",
    "Grouping the tenure, monthly charge and total charge column into different segments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "id": "5krjd8qlykL8",
    "tags": [
     "block:feature_engineering",
     "prev:transform_data"
    ]
   },
   "outputs": [],
   "source": [
    "def yearly_tenure(tenure):\n",
    "  if tenure <= 12:\n",
    "      return 1\n",
    "  elif tenure >12 and tenure <=24:\n",
    "      return 2\n",
    "  elif tenure >24 and tenure <=36:\n",
    "      return 3\n",
    "  elif tenure >36 and tenure <=48:\n",
    "      return 4\n",
    "  elif tenure >48 and tenure <=60:\n",
    "      return 5\n",
    "  elif tenure > 60 and tenure <=72:\n",
    "      return 6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "id": "-hvC86Mu7nen",
    "tags": []
   },
   "outputs": [],
   "source": [
    "def monthly_charge_plan(charge):\n",
    "  if charge <= 35:\n",
    "      return 'Basic'\n",
    "  elif charge>35 and charge <= 80:\n",
    "      return 'Advanced'\n",
    "  elif charge>80:\n",
    "      return 'Premium'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "id": "C2Bwti3C_VPO",
    "tags": []
   },
   "outputs": [],
   "source": [
    "def total_charge_status(charge):\n",
    "  if charge <= 250:\n",
    "      return 'V-low'\n",
    "  elif charge > 250 and charge <= 450:\n",
    "      return 'low'\n",
    "  elif charge > 450 and charge <= 1500:\n",
    "      return 'medium'\n",
    "  elif charge > 1500 and charge <= 3500:\n",
    "      return 'High'\n",
    "  elif charge > 3500:\n",
    "      return 'V-High'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "id": "TEjGUbc_ATTf",
    "tags": []
   },
   "outputs": [],
   "source": [
    "# generating new features\n",
    "data['OnlineSecurityBackup'] = data['OnlineSecurity'] + data['OnlineBackup']\n",
    "data['OnlineSecurityDevice'] = data['OnlineSecurity'] + data['DeviceProtection']\n",
    "data['Streaming'] = data['StreamingMovies'] + data['StreamingTV']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "id": "APEOaQtABFCK",
    "tags": []
   },
   "outputs": [],
   "source": [
    "# applying grouping functions to create new features\n",
    "data['yearly_tenure'] = data['tenure'].apply(yearly_tenure)\n",
    "data['MonthlyChargesplan'] = data['MonthlyCharges'].apply(monthly_charge_plan)\n",
    "data['TotalChargestatus'] = data['TotalCharges'].apply(total_charge_status)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "id": "3z5i1hvGBKHR",
    "tags": []
   },
   "outputs": [],
   "source": [
    "# drop customerID\n",
    "data = data.drop('customerID', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "id": "DO0vJVpHDXlg",
    "tags": []
   },
   "outputs": [],
   "source": [
    "# scale 'MonthlyCharges' and 'TotalCharges' columns\n",
    "scaler = MinMaxScaler()\n",
    "data[['MonthlyCharges', 'TotalCharges']] = scaler.fit_transform(data[['MonthlyCharges', 'TotalCharges']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "id": "tWkduWjGJlMJ",
    "tags": []
   },
   "outputs": [],
   "source": [
    "# one-hot encode categorical variables \n",
    "X = pd.get_dummies(data.drop(columns=['Churn']), drop_first=True)\n",
    "y= data['Churn']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "id": "ZP0OQAZSOqnZ",
    "tags": [
     "block:"
    ]
   },
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=22, stratify=y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "F0tD_7fKkw2J",
    "tags": []
   },
   "source": [
    "# Modelling\n",
    "\n",
    "## Catboost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "id": "zYkYLyjSOwZM",
    "tags": [
     "block:catboost_modeling",
     "prev:feature_engineering"
    ]
   },
   "outputs": [],
   "source": [
    "# compute class weight to handle imbalance nature\n",
    "class_weight = dict(zip(np.unique(y), class_weight.compute_class_weight('balanced',\n",
    "                                                 classes=np.unique(y), y=y))) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "dGxfkD6fO0Jx",
    "outputId": "b45d9571-5d27-454c-863d-bee122da1924",
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0:\ttest: 0.8289318\tbest: 0.8289318 (0)\ttotal: 51.2ms\tremaining: 7.62s\n",
      "20:\ttest: 0.8536616\tbest: 0.8536616 (20)\ttotal: 109ms\tremaining: 668ms\n",
      "40:\ttest: 0.8535645\tbest: 0.8536616 (20)\ttotal: 172ms\tremaining: 458ms\n",
      "60:\ttest: 0.8532652\tbest: 0.8536616 (20)\ttotal: 225ms\tremaining: 328ms\n",
      "80:\ttest: 0.8521779\tbest: 0.8536616 (20)\ttotal: 278ms\tremaining: 237ms\n",
      "100:\ttest: 0.8510674\tbest: 0.8536616 (20)\ttotal: 333ms\tremaining: 161ms\n",
      "120:\ttest: 0.8494486\tbest: 0.8536616 (20)\ttotal: 387ms\tremaining: 92.6ms\n",
      "140:\ttest: 0.8474856\tbest: 0.8536616 (20)\ttotal: 441ms\tremaining: 28.1ms\n",
      "149:\ttest: 0.8467873\tbest: 0.8536616 (20)\ttotal: 466ms\tremaining: 0us\n",
      "\n",
      "bestTest = 0.8536615707\n",
      "bestIteration = 20\n",
      "\n",
      "Shrink model to first 21 iterations.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<catboost.core.CatBoostClassifier at 0x7f9b26de9710>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# initialization\n",
    "cb=CatBoostClassifier(class_weights=class_weight, n_estimators=150,\n",
    "                      eval_metric='AUC', learning_rate=0.1043242,\n",
    "                      max_depth=5, use_best_model=True, random_state=22, \n",
    "                      allow_writing_files=False, metric_period=20)\n",
    "\n",
    "# fitting\n",
    "cb.fit(X_train, y_train, eval_set=(X_test, y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "id": "SmZwqop2hhaf",
    "tags": []
   },
   "outputs": [],
   "source": [
    "# predict\n",
    "cb_pred = cb.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 295
    },
    "id": "52UqmUJsPXgs",
    "outputId": "707d737a-7eaf-4163-a02a-ffb30f1fe846",
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot confusion_matrix\n",
    "cb_cm = confusion_matrix(y_test, cb_pred)\n",
    "sns.heatmap(cb_cm, fmt='g', cbar=False, annot=True, cmap='Blues')\n",
    "plt.title('confusion_matrix')\n",
    "plt.ylabel('True label')\n",
    "plt.xlabel('Predicted label')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "pAdRlNTmlBt6",
    "tags": []
   },
   "source": [
    "## Xgboost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "HaZu5lobSc1r",
    "outputId": "935ad999-c5ac-4237-e619-1c34bf0d7972",
    "tags": [
     "block:xgboost_modeling",
     "prev:feature_engineering"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[14:21:00] WARNING: ../src/learner.cc:576: \n",
      "Parameters: { \"metrics\", \"silent\" } might not be used.\n",
      "\n",
      "  This could be a false alarm, with some parameters getting used by language bindings but\n",
      "  then being mistakenly passed down to XGBoost core, or some parameter actually being used\n",
      "  but getting flagged wrongly here. Please open an issue if you find any such cases.\n",
      "\n",
      "\n",
      "[14:21:01] WARNING: ../src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n",
      "[0]\tvalidation_0-logloss:0.65247\tvalidation_1-logloss:0.65756\n",
      "[50]\tvalidation_0-logloss:0.30319\tvalidation_1-logloss:0.46641\n",
      "[100]\tvalidation_0-logloss:0.24431\tvalidation_1-logloss:0.47187\n",
      "[108]\tvalidation_0-logloss:0.23954\tvalidation_1-logloss:0.47214\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=0.8,\n",
       "              colsample_bynode=1, colsample_bytree=1, enable_categorical=False,\n",
       "              gamma=0, gpu_id=-1, importance_type=None,\n",
       "              interaction_constraints='', learning_rate=0.1043242,\n",
       "              max_delta_step=0, max_depth=10, metrics='auc', min_child_weight=1,\n",
       "              missing=nan, monotone_constraints='()', n_estimators=600,\n",
       "              n_jobs=16, num_parallel_tree=1, predictor='auto', random_state=22,\n",
       "              reg_alpha=0.8, reg_lambda=1, scale_pos_weight=0.3627, silent=True,\n",
       "              subsample=1, tree_method='exact', validate_parameters=1,\n",
       "              verbosity=None)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# initialization\n",
    "xgb=XGBClassifier(scale_pos_weight=0.3627, max_depth=10, \n",
    "                  learning_rate=0.1043242, n_estimators=600, \n",
    "                  colsample_bylevel=0.8, reg_alpha=0.8,\n",
    "                  silent=True, metrics='auc', random_state=22)\n",
    "# fitting\n",
    "xgb.fit(X_train,y_train,eval_set=[(X_train,y_train),(X_test, y_test)], early_stopping_rounds=50,verbose=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "id": "IKsFoE0kS-GY",
    "tags": []
   },
   "outputs": [],
   "source": [
    "# predict\n",
    "xgb_pred = xgb.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 295
    },
    "id": "z-3e7LUNTEeB",
    "outputId": "cd835a5e-5434-4e8b-d55d-6a1dc54a4a9d",
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot confusion_matrix\n",
    "xgb_cm = confusion_matrix(y_test, xgb_pred)\n",
    "sns.heatmap(xgb_cm, fmt='g', cbar=False, annot=True, cmap='Blues')\n",
    "plt.title('confusion_matrix')\n",
    "plt.ylabel('True label')\n",
    "plt.xlabel('Predicted label')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "OuZbR8G9mMsM",
    "tags": []
   },
   "source": [
    "## LightGBM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "0bQMgEEAZP6G",
    "outputId": "f394edc6-3508-41df-d1ac-35895c97a1ac",
    "tags": [
     "block:lightgbm_modeling",
     "prev:feature_engineering"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LGBMClassifier(random_state=22, scale_pos_weight=0.362)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# initialization\n",
    "lgbm = LGBMClassifier(random_state=22,scale_pos_weight=0.362)\n",
    "\n",
    "# fitting\n",
    "lgbm.fit(X_train, y_train, categorical_feature = 'auto', eval_set=(X_test, y_test),feature_name='auto', verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "id": "BT0xIfLwakfC",
    "tags": []
   },
   "outputs": [],
   "source": [
    "# predict\n",
    "lgbm_pred = lgbm.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 295
    },
    "id": "W-yjbgQ6blhX",
    "outputId": "0adf1d6b-626f-4708-8b6d-042c8908cecd",
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot confusion matrix\n",
    "lgbm_cm = confusion_matrix(y_test, lgbm_pred)\n",
    "sns.heatmap(lgbm_cm, fmt='g', cbar=False, annot=True, cmap='Blues')\n",
    "plt.title('confusion_matrix')\n",
    "plt.ylabel('True label')\n",
    "plt.xlabel('Predicted label')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_Vnxkq9OmlqA",
    "tags": []
   },
   "source": [
    "## Ensembling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "id": "QBSR17E-kqbC",
    "tags": [
     "block:ensembling",
     "prev:xgboost_modeling",
     "prev:catboost_modeling",
     "prev:lightgbm_modeling"
    ]
   },
   "outputs": [],
   "source": [
    "predictions = np.array([cb_pred, xgb_pred, lgbm_pred])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "id": "Q0QOVmbAmn3N",
    "tags": []
   },
   "outputs": [],
   "source": [
    "pred_mode = stats.mode(predictions, axis=0)[0][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 295
    },
    "id": "ywPxzaHznZdq",
    "outputId": "98d33cb1-1db3-49ed-a193-e05a73efccd3",
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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mqqHA37vJqpAkVdxKAz+lNKcpC5EkVdZnvnmaJKl5MvAlKRMGviRlwsCXpEwY+JKUCQNfkjJh4EtSJgx8ScqEgS9JmTDwJSkTBr4kZcLAl6RMGPiSlAkDX5IyYeBLUiYMfEnKhIEvSZkw8CUpEwa+JGXCwJekTBj4kpQJA1+SMmHgS1Im2lS7AP3rZs94jyt/dh4fzJ0DAXvvdzD7Hnw4U//xGtdcfjEfLllM9w03ZviZP6ZDx04ATJ38Otf88qcsXryQVtGKC0ddR9u2a1f5SNQSDT98CMd+dTcigt+NfoJRNz3C9lv25H/OOYyO7ddm6vTZHHvOdSxY9CG9N+7GC6N/wGtTZwAw/u9TOOWiW6p8BC2Hgd8CtGrdhq8P+w59t+jPksWLOHv40Ww/cGeuuvRCjhx2Ktvs8Dkevncsf7ztBv7zGydRW1vDFf91LsO/fz59Nt+SBfPn0aa1LwU1vm0235hjv7obexz1Mz5eWsvYK07mnscn8f/PPYIzL72Tcc++wdEH7sJpx+zNBVf+CYDJ02axy2EXV7nylskhnRag63rr03eL/gC079CRnr03Zc6smbw77S223n4gADsMHMT4cQ8D8Ldnn6Z333702XxLANbpvC6tWreuTvFq0fr33YhnJk1hyYdLqa2t4/Fn3+CgoQPo13sDxj37BgAPPfUKB+09oLqFZsLAb2FmvjedKW+8Sr/+29Jr082Y8NdHAXjqsQeZPfN9AN6dNpWI4KdnjeCsk7/O2Fuvr2bJasFe/Md0Bu/Uj25dOtK+3Vrss/u29NqoKy9PfpcDhuwAwFf/bSC9Nuz6yXM27bkeT948kvuuPpXBO21erdJbpCYP/Ig4toFlwyJiQkRMGH3T75qyrBbhwyWLufSCkRx90nfp0LET3/ruudx/9+2cffJRLFmymDZt1gKgrraWVydNZPiZP+a8X1zNhCceYdLz46tcvVqiV998n0uuvZ+7rxzO2CuGM/HVadTW1vGt837PsP/cgyd+/306dVibj5fWAvDerPlsue+57Hr4fzHyktFc+5NvsE7HdlU+ipajGgO35wMrTPOU0lXAVQDPTZ2fmrKo5q6mpoZLLxjJ4KH7MGj3oQD07L0pZ188Cij16l8YPw6AbutvSP/td6Jzl3UBGPCF3Xjz9VfZbqdBValdLdt1Y57kujFPAnD+tw/gnffn8dqU9zng5CsA6Nd7A/bdY1sAPl5aw5wPagB4/uW3mTxtFlv02YDnXnqrOsW3MBXp4UfE31by+DuwYSX2mbOUElf94sf06L0p+x9y5CftH8ydA0BdXR133vRb9t7/awDs8PldeHvKG3z04YfU1tbw8t+fo2efvlWpXS1f966lK8M22agrBw7dkT/8ecInbRHBmd/8Er+5vdQZWb9rJ1q1CqA0tNOvd3fenDarOoW3QJXq4W8IfAmYu1x7AH+t0D6z9eqLE3n8gXvYpG8/zjzxCAAOPW44773zFveNvR2AQbsPYciXDgCg0zqd2e+rR3DOiKMJggGDBjNw592rVr9atpt/fgLd1u3I0ppavnPxrXywcAnDDx/Ctw7dE4C7HnqB6+96CoDdB/bjhyftz9KaWurqEiMuuoW58xdXs/wWJVJq/JGTiLgG+F1KadwKlt2UUjpiVdtwSEdrqsEHnV3tEqSVWvL8qFjZsor08FNKxzewbJVhL0lqfF6WKUmZMPAlKRMGviRlwsCXpEwY+JKUCQNfkjJh4EtSJgx8ScqEgS9JmTDwJSkTBr4kZcLAl6RMGPiSlAkDX5IyYeBLUiYMfEnKhIEvSZkw8CUpEwa+JGXCwJekTBj4kpQJA1+SMmHgS1ImDHxJyoSBL0mZMPAlKRMGviRlwsCXpEwY+JKUCQNfkjJh4EtSJgx8ScqEgS9JmTDwJSkTBr4kZcLAl6RMGPiSlAkDX5IyYeBLUiYMfEnKhIEvSZkw8CUpEwa+JGXCwJekTBj4kpQJA1+SMmHgS1ImDHxJyoSBL0mZiJRStWtQE4iIYSmlq6pdh7Q8X5tNxx5+PoZVuwBpJXxtNhEDX5IyYeBLUiYM/Hw4Rqo1la/NJuJJW0nKhD18ScqEgS9JmTDwW7iI2CciXo2INyLizGrXIy0TEb+NiBkRManateTCwG/BIqI1cAWwL7ANcHhEbFPdqqRPXAvsU+0icmLgt2yDgDdSSpNTSh8DtwAHVrkmCYCU0mPAnGrXkRMDv2XrCbxdb35a0SYpQwa+JGXCwG/Z3gE2qTffq2iTlCEDv2V7BtgiIvpGRFvgMGBslWuSVCUGfguWUqoBvg38BXgZuDWl9GJ1q5JKIuJm4Elgq4iYFhHHV7umls5bK0hSJuzhS1ImDHxJyoSBL0mZMPAlKRMGviRlwsDXGi8iaiPihYiYFBG3RUSHf2Fb10bEIcX01Q3dTC4ihkTEbquxjykRsX657cuts/Az7uu8iDj9s9aoPBn4ag6WpJQGpJS2Az4GTqy/MCLarM5GU0onpJReamCVIcBnDnxpTWXgq7l5HOhX9L4fj4ixwEsR0ToifhYRz0TE3yLiWwBRMqr4TYAHgA2WbSgiHomIzxfT+0TEcxExMSIejIhNKb2xnFZ8utgjIrpHxB3FPp6JiMHFc9eLiPsi4sWIuBqIVR1ERIyJiGeL5wxbbtmlRfuDEdG9aNs8Iu4tnvN4RPRvlL+msrJaPSOpGoqe/L7AvUXTQGC7lNKbRWh+kFL6QkSsDTwREfcBOwFbUfo9gA2Bl4DfLrfd7sBvgD2LbXVLKc2JiF8BC1NKPy/Wuwm4NKU0LiJ6U/oG89bAj4BxKaULImJ/oJxvjB5X7KM98ExE3JFSmg10BCaklE6LiHOLbX+b0g99n5hSej0idgauBIauxp9RGTPw1Ry0j4gXiunHgWsoDbWMTym9WbT/O7DDsvF5oAuwBbAncHNKqRaYHhEPrWD7uwCPLdtWSmll92j/IrBNxCcd+M4R0anYx1eL5/4pIuaWcUynRMTBxfQmRa2zgTrgD0X7jcDoYh+7AbfV2/faZexD+hQDX83BkpTSgPoNRfAtqt8EjEgp/WW59fZrxDpaAbuklD5cQS1li4ghlN48dk0pLY6IR4B2K1k9Ffudt/zfQPqsHMNXS/EX4KSIWAsgIraMiI7AY8ChxRj/xsBeK3juU8CeEdG3eG63on0BsE699e4DRiybiYgBxeRjwBFF275A11XU2gWYW4R9f0qfMJZpBSz7lHIEpaGi+cCbEfEfxT4iInZcxT6k/8PAV0txNaXx+eeKH8X+NaVPsHcCrxfLrqd0d8ZPSSnNBIZRGj6ZyD+HVO4GDl520hY4Bfh8cVL4Jf55tdD5lN4wXqQ0tPPWKmq9F2gTES8DF1N6w1lmETCoOIahwAVF+5HA8UV9L+JPVWo1eLdMScqEPXxJyoSBL0mZMPAlKRMGviRlwsCXpEwY+JKUCQNfkjLxv96U9CXqWP0FAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot confusion matrix\n",
    "ens_cm = confusion_matrix(y_test, pred_mode)\n",
    "sns.heatmap(ens_cm, fmt='g', cbar=False, annot=True, cmap='Blues')\n",
    "plt.title('confusion_matrix')\n",
    "plt.ylabel('True label')\n",
    "plt.xlabel('Predicted label')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "telco-customer-churn-orig.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "kubeflow_notebook": {
   "autosnapshot": true,
   "experiment": {
    "id": "new",
    "name": "telco"
   },
   "experiment_name": "telco",
   "katib_metadata": {
    "algorithm": {
     "algorithmName": "grid"
    },
    "maxFailedTrialCount": 3,
    "maxTrialCount": 12,
    "objective": {
     "objectiveMetricName": "",
     "type": "minimize"
    },
    "parallelTrialCount": 3,
    "parameters": []
   },
   "katib_run": false,
   "pipeline_description": "analyze behavior to retain customers and predict churning",
   "pipeline_name": "telco-customer-churn-pipeline",
   "snapshot_volumes": true,
   "steps_defaults": [
    "label:access-ml-pipeline:true",
    "label:access-rok:true"
   ],
   "volume_access_mode": "rwm",
   "volumes": [
    {
     "annotations": [],
     "mount_point": "/home/jovyan",
     "name": "telco-workspace-2w4lb",
     "size": 5,
     "size_type": "Gi",
     "snapshot": false,
     "type": "clone"
    }
   ]
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
